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3 Pandas Introduction (1).ipynb.html
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3 Pandas Introduction (1).ipynb</font>
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<pre><span class="s0">{</span>
<span class="s2">"cells"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"486ce2fd"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"# Introuction to Pandas</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<img src=</span><span class="s3">\"</span><span class="s2">https://user-images.githubusercontent.com/7065401/75165824-badf4680-5701-11ea-9c5b-5475b0a33abf.png</span><span class="s3">\"\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" style=</span><span class="s3">\"</span><span class="s2">width:300px; float: right; margin: 0 40px 40px 40px;</span><span class="s3">\"</span><span class="s2">></img></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"# Pandas - Series</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<br></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"`Pandas` is one of the most preferred tools for data scientists to do data manipulation and analysis, next to `matplotlib` for data visualization and `NumPy`, the fundamental library for scientific computing in Python on which Pandas was built"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">1</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"941ea8af"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"import numpy as np</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"import pandas as pd"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">2</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b25abc01"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"0 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"5 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"6 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">2</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"# In millions</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"g7_pop = pd.Series([35.467, 63.951, 80.940, 60.665, 127.061, 64.511, 318.523])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">3</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"834d918b"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"pandas.core.series.Series"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">3</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"type(g7_pop)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">4</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"2b192090"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"0 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"5 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"6 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">4</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.name = 'G7 population in millions'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">5</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"0297e632"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"dtype('float64')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">5</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.dtype"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">6</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"e861a0cb"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"array([ 35.467, 63.951, 80.94 , 60.665, 127.061, 64.511, 318.523])"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">6</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.values"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">7</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"abd09507"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"numpy.ndarray"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">7</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"type(g7_pop.values)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">8</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"d49426ad"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"name"</span><span class="s0">: </span><span class="s2">"stdout"</span><span class="s0">,</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"stream"</span><span class="s0">,</span>
<span class="s2">"text"</span><span class="s0">: [</span>
<span class="s2">"35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"63.951</span><span class="s3">\n</span><span class="s2">"</span>
<span class="s0">]</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"print(g7_pop[0])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"print(g7_pop[1])"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">9</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"5a8a571f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"RangeIndex(start=0, stop=7, step=1)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">9</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.index"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">10</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"1edee53e"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"0 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"5 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"6 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">10</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">11</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"266291e7"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">11</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.index = [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Canada',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'France',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Germany',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Italy',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Japan',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United Kingdom',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United States'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"]</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">12</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"c020b54e"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>G7 population in millions</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" G7 population in millions</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">12</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.to_frame()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"44b4abc3"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Combining everything into a single command"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ea880bb9"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 Population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">13</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7 = pd.Series({</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Canada' : 35.467,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'France' : 63.951,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Germany' : 80.94,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Italy' : 60.665,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Japan' : 127.061,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United Kingdom' : 64.511,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United States' : 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"}, name = 'G7 Population in millions')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"g7"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">14</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ca7ef681"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"G7 = pd.Series(</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" [35.467, 63.951, 80.940, 60.665, 127.061, 64.511, 318.523],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" index=['Canada', 'France', 'Germany', 'Italy', 'Japan', 'United Kingdom', 'United States'],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" name = 'G7 population in millions'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">")"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"8663579a"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Indexing</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Indexing works similarly to lists and dictionaries, you use the **index** of the element you're looking for:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">15</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"16560c39"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">15</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"G7"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">16</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"be15213f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Spain NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">16</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"pd.Series(g7_pop, index = ['Canada', 'France', 'Germany', 'Spain'])"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">17</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"22c706b5"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">17</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">18</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"fac4e553"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"127.061"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">18</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop['Japan']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">19</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"728b791a"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"80.94"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">19</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop['Germany']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">20</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"dabbe147"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">20</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.iloc[[0, 1]]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">21</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"1afa5cde"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"318.523"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">21</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.iloc[-1]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">22</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"7bc77ee7"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"(80.94, 64.511)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">22</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.iloc[2], g7_pop.iloc[-2]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">23</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"f305f73f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">23</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[['Italy', 'France']]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">24</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ab57cbf9"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">24</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop['Canada':'Italy']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"171ec1aa"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Conditional selection (boolean arrays)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"The same boolean array techniques we saw applied to numpy arrays can be used for Pandas `Series`:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">25</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"28cbbe92"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">25</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">26</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"4a5665f5"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada False</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France False</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany True</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy False</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan True</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom False</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States True</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: bool"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">26</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop > 80"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">27</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ec865d7c"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">27</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[g7_pop > 80]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b36982b8"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Statistics"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">28</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"63376bde"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"107.30257142857144"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">28</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.mean()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">29</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"1c9efcc7"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"64.511"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">29</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.median()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">30</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"6e8588b1"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">30</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[~(g7_pop > g7_pop.mean())]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">31</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"8039d8e9"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"97.24996987121581"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">31</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.std()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">32</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b16f51da"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">32</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[g7_pop>g7_pop.mean()]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">33</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"f8ee331d"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">33</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[(g7_pop > g7_pop.mean()-g7_pop.std()/2) | (g7_pop > g7_pop.mean() + g7_pop.std()/2)]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"252e8c8b"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Operations and methods</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Series also support vectorized operations and aggregation functions as Numpy:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">34</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"8f0c87a4"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">34</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">35</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"41f57dd6"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35467000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63951000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80940000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60665000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127061000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64511000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318523000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">35</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop * 1_000_000"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">36</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"f97d1d85"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"107.30257142857144"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">36</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.mean()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">37</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"52992d64"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"60.25575"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">37</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop['Canada':'Italy'].mean()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"0636da0d"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Boolean arrays</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"(Work in the same way as numpy)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">38</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"c52e1648"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 3.568603</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 4.158117</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 4.393708</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 4.105367</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 4.844667</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 4.166836</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 5.763695</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">38</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"np.log(g7_pop)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">39</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"1c8aa05f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 35.467</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">39</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[(g7_pop > 80)|(g7_pop<40)]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"31477e12"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Modifying series"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">40</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"7c53e82e"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop['Canada'] = 40.5"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">41</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"7366665a"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop.iloc[-1] = 500"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">42</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b2e92d66"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 40.500</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 500.000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">42</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">43</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a776d129"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop[g7_pop < 70] = 99.99"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">44</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"23d8eb81"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Canada 99.990</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 99.990</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 99.990</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 99.990</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 500.000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: G7 population in millions, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">44</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"g7_pop"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s3">null</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a39ce4b2"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: []</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s3">null</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"d0ef3998"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: []</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"3c2c34c4"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"# Pandas - `DataFrame`s</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<img src=</span><span class="s3">\"</span><span class="s2">https://user-images.githubusercontent.com/7065401/75165824-badf4680-5701-11ea-9c5b-5475b0a33abf.png</span><span class="s3">\"\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" style=</span><span class="s3">\"</span><span class="s2">width:300px; float: right; margin: 0 40px 40px 40px;</span><span class="s3">\"</span><span class="s2">></img></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Probably the most important data structure of pandas is the `DataFrame`. It's a tabular structure tightly integrated with `Series`.<br></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<br></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"A `DataFrame` is a general 2D labeled, size-mutable tabular structure with potentially heterogeneously typed coloumns. Building and handling two or more dimensional arrays is atedious task, burden is placed on the user to consider the orientation of the data set when writing functions. But using Pandas data structures, the mental effort of the user is reduced.<br></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<br></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Creating `DataFrame`s manually can be tedious. 99% of the time you'll be pulling the data from a Database, a csv file or the web. But still, you can create a DataFrame by specifying the columns and values:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">45</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"481a93b1"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"import numpy as np</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"import pandas as pd"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">46</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"91a8bb35"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>0</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>3</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>4</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>5</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>6</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"0 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"5 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"6 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">"df = pd.DataFrame({</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Population': [35.467, 63.951, 80.94 , 60.665, 127.061, 64.511, 318.523],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'GDP' : [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 1785387,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 2833687,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 3874437,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 2167744,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 4602367,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 2950039,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 17348075</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Surface Area': [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 9984670,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 640679,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 357114,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 301336,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 377930,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 242495,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 9525067</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'HDI': [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.913,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.888,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.916,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.873,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.891,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.907,</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0.915</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Continent': [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'America',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Europe',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Europe',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Europe',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Asia',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Europe',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'America'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ]</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"}, columns = ['Population', 'GDP', 'Surface Area', 'HDI', 'Continent'])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
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<span class="s0">{</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s2">"`DataFrame`s also have indexes. As you can see in the </span><span class="s3">\"</span><span class="s2">table</span><span class="s3">\" </span><span class="s2">above, pandas has assigned a numeric, autoincremental index automatically to each </span><span class="s3">\"</span><span class="s2">row</span><span class="s3">\" </span><span class="s2">in our DataFrame. In our case, we know that each row represents a country, so we'll just reassign the index:"</span>
<span class="s0">]</span>
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<span class="s0">{</span>
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<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Europe 0.571429</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"America 0.285714</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Asia 0.142857</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: Continent, dtype: float64"</span>
<span class="s0">]</span>
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<span class="s2">"df['Continent'].value_counts('Europe')"</span>
<span class="s0">]</span>
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<span class="s2">"df.index = [</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Canada',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'France',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Germany',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Italy',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Japan',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United Kingdom',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United States',]"</span>
<span class="s0">]</span>
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<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">" # Column Non-Null Count Dtype </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"--- ------ -------------- ----- </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 0 Population 7 non-null float64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" 2 Surface Area 7 non-null int64 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 3 HDI 7 non-null float64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 4 Continent 7 non-null object </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"dtypes: float64(2), int64(2), object(1)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"memory usage: 336.0+ bytes</span><span class="s3">\n</span><span class="s2">"</span>
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<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>count</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000e+00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000e+00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>107.302571</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.080248e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.061327e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.900429</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>std</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>97.249970</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.494020e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4.576187e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.016592</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>min</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1.785387e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.424950e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>25%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>62.308000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.500716e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.292250e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.889500</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>50%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.950039e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.779300e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>75%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>104.000500</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4.238402e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.082873e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.914000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>max</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1.734808e+07</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9.984670e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"count 7.000000 7.000000e+00 7.000000e+00 7.000000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"mean 107.302571 5.080248e+06 3.061327e+06 0.900429</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"std 97.249970 5.494020e+06 4.576187e+06 0.016592</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"min 35.467000 1.785387e+06 2.424950e+05 0.873000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"25% 62.308000 2.500716e+06 3.292250e+05 0.889500</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"50% 64.511000 2.950039e+06 3.779300e+05 0.907000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"75% 104.000500 4.238402e+06 5.082873e+06 0.914000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"max 318.523000 1.734808e+07 9.984670e+06 0.916000"</span>
<span class="s0">]</span>
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<span class="s0">]</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
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<span class="s2">"Population float64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"GDP int64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Surface Area int64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"HDI float64</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Continent object</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"dtype: object"</span>
<span class="s0">]</span>
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<span class="s0">}</span>
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<span class="s0">]</span>
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<span class="s0">]</span>
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<span class="s0">{</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Indexing, Selection and Slicing</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Individual columns in the DataFrame can be selected with regular indexing. Each column is represented as a `Series`:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">58</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
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<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" Population GDP</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" Population GDP HDI</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 0.888</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 0.916</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 0.873"</span>
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<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
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<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">72</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"6dfaac89"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 Europe"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">72</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.iloc[1:3,[0,1,4]]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">73</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a3d53224"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" GDP Surface Area HDI</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 2833687 640679 0.888</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 3874437 357114 0.916</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 2167744 301336 0.873"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">73</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.iloc[1:4,1:4]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"dc8d8f29"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Conditional selection (boolean arrays)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"We saw conditional selection applied to `Series` and it'll work in the same way for `DataFrame`s. After all, a `DataFrame` is a collection of `Series`:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">74</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ca3951d0"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</div>"</span>
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<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
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<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">}</span>
<span class="s0">],</span>
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<span class="s2">"df.loc[df['Population'] > 70, 'Population'].to_frame()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"db1db102"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Dropping stuff</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Opposed to the concept of selection, we have </span><span class="s3">\"</span><span class="s2">dropping</span><span class="s3">\"</span><span class="s2">. Instead of pointing out which values you'd like to _select_ you could point which ones you'd like to `drop`:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"3168f098"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">78</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.drop('Canada')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">79</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a679fbb1"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
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<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" GDP Surface Area Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 1785387 9984670 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 2833687 640679 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 3874437 357114 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 2167744 301336 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 4602367 377930 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" GDP Surface Area Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 1785387 9984670 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 2833687 640679 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 3874437 357114 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 2167744 301336 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 4602367 377930 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 2950039 242495 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 17348075 9525067 America"</span>
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<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" GDP Surface Area Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 1785387 9984670 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 2833687 640679 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 3874437 357114 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 2167744 301336 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 4602367 377930 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 2950039 242495 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 17348075 9525067 America"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s0">],</span>
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<span class="s2">"df.drop(['Population', 'HDI'], axis = 'columns')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.drop(['United States', 'Italy'], axis = 'rows')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</div>"</span>
<span class="s0">],</span>
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<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America"</span>
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<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</div>"</span>
<span class="s0">],</span>
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<span class="s2">" Population GDP</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075"</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.35467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17853.87</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.63951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>28336.87</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.80940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>38744.37</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.60665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>21677.44</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1.27061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>46023.67</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.64511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>29500.39</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.18523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>173480.75</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 0.35467 17853.87</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 0.63951 28336.87</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 0.80940 38744.37</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 0.60665 21677.44</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 1.27061 46023.67</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 0.64511 29500.39</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 3.18523 173480.75"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">88</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df[['Population', 'GDP']]/100"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"758ce371"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"**Operations with Series** work at a column level, broadcasting down the rows"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">89</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"e11ffb54"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"GDP -1000000.0</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"HDI -0.3</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">89</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"crisis = pd.Series([-1_000_000, -0.3], index = ['GDP', 'HDI'])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"crisis"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">90</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b692e312"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"name"</span><span class="s0">: </span><span class="s2">"stdout"</span><span class="s0">,</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"stream"</span><span class="s0">,</span>
<span class="s2">"text"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America</span><span class="s3">\n</span><span class="s2">"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>785387.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.613</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1833687.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.588</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2874437.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.616</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1167744.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.573</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3602367.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.591</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1950039.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.607</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>16348075.0</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.615</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" GDP HDI</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 785387.0 0.613</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 1833687.0 0.588</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 2874437.0 0.616</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 1167744.0 0.573</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 3602367.0 0.591</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 1950039.0 0.607</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 16348075.0 0.615"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">90</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"print(df)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df[['GDP', 'HDI']] + crisis"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"bf3292f3"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Modifying DataFrames</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"It's simple and intuitive, You can add columns, or replace values for columns without issues:</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"### Adding a new column"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">91</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"71c75cc1"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"France French</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany German</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy Italian</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: Language, dtype: object"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">91</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"langs = pd.Series(</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ['French', 'German', 'Italian'], </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" index = ['France', 'Germany', 'Italy'], </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" name = 'Language')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"langs"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">92</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"c5bfd717"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>French</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>German</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Italian</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent Language</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe French</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe German</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe Italian</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America NaN"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">92</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df['Language'] = langs</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">93</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"5a3c4982"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>French</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>German</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Italian</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>NaN</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent Language</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe French</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe German</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe Italian</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe NaN</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America NaN"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">93</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.loc['Canada', 'Language'] = 'English'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"16f32603"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"---</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"### Replacing values per column"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">94</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"62976804"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>HDI</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United Kingdom</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>United States</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area HDI Continent Language</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United Kingdom 64.511 2950039 242495 0.907 Europe English</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"United States 318.523 17348075 9525067 0.915 America English"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">94</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df['Language'] = 'English'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"8ac7f743"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"---</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"### Renaming Columns"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">95</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"813f6a73"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df = df.rename(</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" columns={</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'HDI':'Human Development Index',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'Annual Popcorn Consumption' : 'APC'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" },</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" index = {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United States' : 'USA',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" 'United Kingdom' : 'UK'</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" })"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">96</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"f8775f8f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>UK</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>USA</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK 64.511 2950039 242495 0.907 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA 318.523 17348075 9525067 0.915 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" Continent Language </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada America English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan Asia English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA America English "</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">96</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">97</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"23c209eb"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>CANADA</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>FRANCE</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GERMANY</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>ITALY</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>JAPAN</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>UK</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>USA</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"CANADA 35.467 1785387 9984670 0.913 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"FRANCE 63.951 2833687 640679 0.888 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"GERMANY 80.940 3874437 357114 0.916 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"ITALY 60.665 2167744 301336 0.873 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"JAPAN 127.061 4602367 377930 0.891 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK 64.511 2950039 242495 0.907 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA 318.523 17348075 9525067 0.915 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" Continent Language </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"CANADA America English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"FRANCE Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"GERMANY Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"ITALY Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"JAPAN Asia English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA America English "</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">97</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.rename(index = str.upper)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"2fa5dd58"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Language</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>france</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"canada 35.467 1785387 9984670 0.913 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"france 63.951 2833687 640679 0.888 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"germany 80.940 3874437 357114 0.916 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"italy 60.665 2167744 301336 0.873 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"japan 127.061 4602367 377930 0.891 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"uk 64.511 2950039 242495 0.907 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"usa 318.523 17348075 9525067 0.915 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"canada America English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"germany Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"italy Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"japan Asia English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"uk Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Uk</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Usa</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>English</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Uk 64.511 2950039 242495 0.907 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Usa 318.523 17348075 9525067 0.915 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"Germany Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan Asia English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Uk Europe English </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"f00d120d"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Dropping columns"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">100</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"57286bc8"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>UK</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>USA</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index Continent</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK 64.511 2950039 242495 0.907 Europe</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA 318.523 17348075 9525067 0.915 America"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">100</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.drop(columns='Language', inplace = True)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"2f7b345e"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Creating columns from other columns</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Altering a DataFrame often involves combining different columns into another. For example, in our Countries analysis, we could try to calculate the </span><span class="s3">\"</span><span class="s2">GDP per capita</span><span class="s3">\"</span><span class="s2">, which is just, `GDP / Population`.</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"The result of that operation is just another series that you can add to the original `DataFrame`:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">101</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"d5e3f667"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP Per Capita</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>50339.385908</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>44310.284437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>47868.013343</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35733.025633</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>36221.712406</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>UK</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2950039</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>242495</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>45729.239975</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>USA</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>17348075</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9525067</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.915</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>54464.120330</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK 64.511 2950039 242495 0.907 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA 318.523 17348075 9525067 0.915 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" Continent GDP Per Capita </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada America 50339.385908 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France Europe 44310.284437 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany Europe 47868.013343 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy Europe 35733.025633 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan Asia 36221.712406 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"UK Europe 45729.239975 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"USA America 54464.120330 "</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">101</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df['GDP Per Capita'] = df['GDP'] / df['Population']</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"753a0f7f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Statistical information"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">102</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"4dc90478"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Continent</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP Per Capita</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Canada</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1785387</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9984670</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.913</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>America</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>50339.385908</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>France</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>63.951</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2833687</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>640679</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.888</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>44310.284437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Germany</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>80.940</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3874437</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>357114</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>47868.013343</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Italy</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>60.665</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2167744</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>301336</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Europe</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35733.025633</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Japan</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>127.061</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4602367</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>377930</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.891</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>Asia</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>36221.712406</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index Continent </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 35.467 1785387 9984670 0.913 America </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 63.951 2833687 640679 0.888 Europe </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 80.940 3874437 357114 0.916 Europe </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 60.665 2167744 301336 0.873 Europe </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 127.061 4602367 377930 0.891 Asia </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" GDP Per Capita </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Canada 50339.385908 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"France 44310.284437 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Germany 47868.013343 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Italy 35733.025633 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Japan 36221.712406 "</span>
<span class="s0">]</span>
<span class="s0">},</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s0">{</span>
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<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Population</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Surface Area</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Human Development Index</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>GDP Per Capita</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>count</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000e+00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000e+00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7.000000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>mean</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>107.302571</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.080248e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.061327e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.900429</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>44952.254576</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>std</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>97.249970</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.494020e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4.576187e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.016592</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6954.983875</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>min</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35.467000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1.785387e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.424950e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.873000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>35733.025633</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>25%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>62.308000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.500716e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.292250e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.889500</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>40265.998421</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>50%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>64.511000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2.950039e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>3.779300e+05</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.907000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>45729.239975</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>75%</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>104.000500</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>4.238402e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>5.082873e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.914000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>49103.699626</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>max</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>318.523000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1.734808e+07</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>9.984670e+06</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>0.916000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>54464.120330</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Population GDP Surface Area Human Development Index </span><span class="s3">\\\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"count 7.000000 7.000000e+00 7.000000e+00 7.000000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"mean 107.302571 5.080248e+06 3.061327e+06 0.900429 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"std 97.249970 5.494020e+06 4.576187e+06 0.016592 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"min 35.467000 1.785387e+06 2.424950e+05 0.873000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"25% 62.308000 2.500716e+06 3.292250e+05 0.889500 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"50% 64.511000 2.950039e+06 3.779300e+05 0.907000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"75% 104.000500 4.238402e+06 5.082873e+06 0.914000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"max 318.523000 1.734808e+07 9.984670e+06 0.916000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" GDP Per Capita </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"count 7.000000 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"mean 44952.254576 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"std 6954.983875 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"min 35733.025633 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"25% 40265.998421 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"50% 45729.239975 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"75% 49103.699626 </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"max 54464.120330 "</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">103</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">}</span>
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<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.describe()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"population = df['Population']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s2">"(35.467, 318.523)"</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
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<span class="s0">}</span>
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<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"population.min(), population.max()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"751.118"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">106</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
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<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"population.sum()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"<Figure size 432x288 with 1 Axes>"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"metadata"</span><span class="s0">: {</span>
<span class="s2">"needs_background"</span><span class="s0">: </span><span class="s2">"light"</span>
<span class="s0">},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"display_data"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"plt.plot(x,x**2)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.plot(x, -1*(x**2))"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">116</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"d38874c7"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Text(0, 0.5, 'Range of (x**2)')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">116</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"image/png"</span><span class="s0">: </span><span 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</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"<Figure size 864x432 with 1 Axes>"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"metadata"</span><span class="s0">: {</span>
<span class="s2">"needs_background"</span><span class="s0">: </span><span class="s2">"light"</span>
<span class="s0">},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"display_data"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"plt.figure(figsize=(12,6))</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.plot(x,x**2)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.plot(x, -1*(x**2))</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.title('My nice plot')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.xlabel('Range of x')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.ylabel('Range of (x**2)')"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">117</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"6f92d0f1"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"import numpy as np</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"import matplotlib.pyplot as plt</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"import pandas as pd</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"%matplotlib inline"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"28422d26"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"Pandas can easily read data stored in different file formats like CSV, JSON, XML or even Excel. Parsing always involves specifying the correct structure, encoding and other details. The `read_csv` method reads CSV files and accepts many parameters."</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">118</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"36316dda"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"# pd.read_csv?"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">119</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"9a3b2370"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-02 00:00:00</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1099.169125</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>0</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-03 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-04 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-05 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>3</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-06 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>4</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-07 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1190.454250</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" 2017-04-02 00:00:00 1099.169125</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"0 2017-04-03 00:00:00 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 2017-04-04 00:00:00 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 2017-04-05 00:00:00 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 2017-04-06 00:00:00 1196.307937</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 2017-04-07 00:00:00 1190.454250"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">119</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df = pd.read_csv('btc-market-price.csv')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df.head()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"b218a277"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"The CSV file we're reading has only two columns: `timestamp` and `price`. It doesn't have a header, it contains whitespaces and has values separated by commas. pandas automatically assigned the first row of data as headers, which is incorrect. We can overwrite this behavior with the `header` parameter:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">120</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"3534fdcf"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-02 00:00:00</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1099.169125</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>0</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-03 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-04 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-05 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>3</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-06 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>4</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-07 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1190.454250</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>...</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>359</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-28 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7960.380000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>360</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-29 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7172.280000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>361</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-30 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6882.531667</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>362</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-31 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6935.480000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>363</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-04-01 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6794.105000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<p>364 rows × 2 columns</p></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" 2017-04-02 00:00:00 1099.169125</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"0 2017-04-03 00:00:00 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 2017-04-04 00:00:00 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 2017-04-05 00:00:00 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 2017-04-06 00:00:00 1196.307937</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 2017-04-07 00:00:00 1190.454250</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">".. ... ...</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"359 2018-03-28 00:00:00 7960.380000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"360 2018-03-29 00:00:00 7172.280000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"361 2018-03-30 00:00:00 6882.531667</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"362 2018-03-31 00:00:00 6935.480000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"363 2018-04-01 00:00:00 6794.105000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"[364 rows x 2 columns]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">120</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
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<span class="s2">"df = pd.read_csv('btc-market-price.csv')</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"809b041f"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"(364, 2)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">121</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.shape"</span>
<span class="s0">]</span>
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<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"We can then set the names of each column explicitely by setting the df.columns attribute:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
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<span class="s2">"data"</span><span class="s0">: {</span>
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<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Timestamp</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Price</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>0</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-03 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>1</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-04 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-05 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>3</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-06 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>4</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-07 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1190.454250</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>...</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>359</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-28 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7960.380000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>360</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-29 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7172.280000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>361</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-30 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6882.531667</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>362</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-31 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6935.480000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>363</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-04-01 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>6794.105000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<p>364 rows × 2 columns</p></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Timestamp Price</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"0 2017-04-03 00:00:00 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"1 2017-04-04 00:00:00 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2 2017-04-05 00:00:00 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"3 2017-04-06 00:00:00 1196.307937</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"4 2017-04-07 00:00:00 1190.454250</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">".. ... ...</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"359 2018-03-28 00:00:00 7960.380000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"360 2018-03-29 00:00:00 7172.280000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"361 2018-03-30 00:00:00 6882.531667</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"362 2018-03-31 00:00:00 6935.480000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"363 2018-04-01 00:00:00 6794.105000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"[364 rows x 2 columns]"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">122</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
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<span class="s2">"df.columns = ['Timestamp', 'Price']</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
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<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th>Timestamp</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Price</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">" <th>1</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-04 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-05 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>3</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-06 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>4</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2017-04-07 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1190.454250</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>...</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>...</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>359</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-28 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7960.380000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>360</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-29 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>7172.280000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>361</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>2018-03-30 00:00:00</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
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<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"ff96334c"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Price</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Timestamp</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-03</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-04</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-05</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-06</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-07</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1190.454250</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Price</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Timestamp </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-03 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-04 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-05 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-06 1196.307937</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-07 1190.454250"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">130</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.head()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">131</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a90f7acd"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Price 1180.023713</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: 2017-04-13 00:00:00, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">131</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.loc['2017-04-13']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"2e10ac82"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"### Putting everything together</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"And now, we've finally arrived to the final, desired version of the `DataFrame` parsed from our CSV file. The steps were:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">132</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"fd3a610c"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Price</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Timestamp</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-02</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1099.169125</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-03</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-04</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-05</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-06</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Price</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Timestamp </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-02 1099.169125</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-03 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-04 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-05 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-06 1196.307937"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">132</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df = pd.read_csv('btc-market-price.csv', header=None)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df.columns = ['Timestamp', 'Price']</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df['Timestamp'] = pd.to_datetime(df['Timestamp'])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df.set_index('Timestamp', inplace = True)</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"df.head()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">133</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a7f80cc6"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df = pd.read_csv('btc-market-price.csv', </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" header=None, </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" names = ['Timestamp', 'Price'], </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" index_col= 0, </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" parse_dates=True)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">134</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"aaa87a57"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/html"</span><span class="s0">: [</span>
<span class="s2">"<div></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<style scoped></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th:only-of-type {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: middle;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe tbody tr th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" vertical-align: top;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" .dataframe thead th {</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" text-align: right;</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" }</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</style></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"<table border=</span><span class="s3">\"</span><span class="s2">1</span><span class="s3">\" </span><span class="s2">class=</span><span class="s3">\"</span><span class="s2">dataframe</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr style=</span><span class="s3">\"</span><span class="s2">text-align: right;</span><span class="s3">\"</span><span class="s2">></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Price</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>Timestamp</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th></th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </thead></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-02</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1099.169125</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-03</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.813000</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-04</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1141.600363</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-05</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1133.079314</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <th>2017-04-06</th></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" <td>1196.307937</td></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tr></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" </tbody></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</table></span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</div>"</span>
<span class="s0">],</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">" Price</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Timestamp </span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-02 1099.169125</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-03 1141.813000</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-04 1141.600363</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-05 1133.079314</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"2017-04-06 1196.307937"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">134</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.head()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">135</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"4555b27e"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"Price 4193.574667</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"Name: 2017-09-29 00:00:00, dtype: float64"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">135</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.loc['2017-09-29']"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"markdown"</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"51851de2"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"## Plotting basics</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"`pandas` integrates with Matplotlib and creating a plot is as simple as:"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">136</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"7e5c0160"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"image/png"</span><span class="s0">: </span><span 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</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"<Figure size 432x288 with 1 Axes>"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"metadata"</span><span class="s0">: {</span>
<span class="s2">"needs_background"</span><span class="s0">: </span><span class="s2">"light"</span>
<span class="s0">},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"display_data"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.plot()</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.show()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">137</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"c4ddb454"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"image/png"</span><span class="s0">: </span><span 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</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"<Figure size 432x288 with 1 Axes>"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"metadata"</span><span class="s0">: {</span>
<span class="s2">"needs_background"</span><span class="s0">: </span><span class="s2">"light"</span>
<span class="s0">},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"display_data"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"plt.plot(df.index, df['Price'])</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"plt.show()"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">138</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"8a9e53ef"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"DatetimeIndex(['2017-04-02', '2017-04-03', '2017-04-04', '2017-04-05',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" '2017-04-06', '2017-04-07', '2017-04-08', '2017-04-09',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" '2017-04-10', '2017-04-11',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" ...</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" '2018-03-23', '2018-03-24', '2018-03-25', '2018-03-26',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" '2018-03-27', '2018-03-28', '2018-03-29', '2018-03-30',</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" '2018-03-31', '2018-04-01'],</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">" dtype='datetime64[ns]', name='Timestamp', length=365, freq=None)"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">138</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"execute_result"</span>
<span class="s0">}</span>
<span class="s0">],</span>
<span class="s2">"source"</span><span class="s0">: [</span>
<span class="s2">"df.index"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s0">{</span>
<span class="s2">"cell_type"</span><span class="s0">: </span><span class="s2">"code"</span><span class="s0">,</span>
<span class="s2">"execution_count"</span><span class="s0">: </span><span class="s4">139</span><span class="s0">,</span>
<span class="s2">"id"</span><span class="s0">: </span><span class="s2">"a04a91bc"</span><span class="s0">,</span>
<span class="s2">"metadata"</span><span class="s0">: {},</span>
<span class="s2">"outputs"</span><span class="s0">: [</span>
<span class="s0">{</span>
<span class="s2">"data"</span><span class="s0">: {</span>
<span class="s2">"image/png"</span><span class="s0">: </span><span 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8zPTaGzvxFqbglGJyGSloCsiIiIiKRWOWPzB/tfoFmSk0RW2tARCKRiZiExWCroiIiIiklL+YDTEDtSMCqDer4ZUIpI4BV0RERERSanWQBdA/2t0Mz0AWqcrIsOioCsiIiIiKdUaGLiiWxCv6CroisgwKOiKiIiISEqdCLr9NKOKBV1VdEVkOBR0RURERCSl4lOXB1ujq6ArIsOhoCsiIiIiKTXY1GWv20mmx0WdmlGJyDAo6IqIiIhISp2o6J48dRmiVV1VdEVkOBR0RURERCSlWgap6IKCrogMn4KuiIiIiKRUS6CLNKcDr9vZ7/MFGWnU+xV0RSRxCroiIiIiklKtgdCA1VxQRVdEhk9BV0RERERSaqigW5Dpob4tiLV2HEclIpOZgq6IiIiIpFRroGvARlQQnbrcFba0BkPjOCoRmcwUdEVEREQkpRKZugzQoHW6IpIgBV0RERERSaloRXeQoJsZDbr1WqcrIglS0BURERGRlIpWdAefugyoIZWIJExBV0RERERSKpFmVAD1/uB4DUlEJjkFXRERERFJmXDE4g8mVtHV1GURSZSCroiIiIikjD/WSTl7kIqu1+0kPc2pqcsikjAFXRERERFJmdZAF8CgU5ch2nlZQVdEEqWgKyIiIiIp0xqIVnQHm7oM0enLmrosIolS0BURERGRlIkH3eyhgm6mR82oRCRhCroiIiIikjKauiwiY0FBV0RERERSJh5e89LTBj0vPnXZWjsewxKRSU5BV0RERERSpjY2Hbkwa/Cgm+1z0xmKEAxFxmNYIjLJKeiKiIiISMrUtgbJ9LhITxt86nJ8+6GW2FRnEZHBDBl0jTG/NsbUGGN29Dh2tzHmtdjXYWPMa7Hj840xHT2eu6XHNeuNMduNMQeMMT8yxpjYcU/sfgeMMZuMMfOT/zZFREREZCKqbQ1SlOUZ8rxsX7RZVbx5lYjIYBKp6N4GXN7zgLX23dbaddbadcD9wB97PF0Wf85a+9Eex38G3AwsiX3F73kj0GitXQz8APj2SN6IiIiIiEw+df4ghZmDT1uGE82qFHRFJBFDBl1r7TNAQ3/Pxaqy7wJ+P9g9jDEzgWxr7Ys22kHgDuCq2NNXArfHHt8HXByv9oqIiIjI1JZoRTe+z26rpi6LSAJGu0b3XKDaWru/x7EFxpitxpinjTHnxo6VAuU9zimPHYs/dwzAWhsCmoGCUY5LRERERCaB2tYgRZmJBN3YGt0OVXRFZGiDr/of2nvoXc2tBOZaa+uNMeuBPxljVgH9VWjjveEHe64XY8zNRKc/M3fu3BEPWkRERERSL9AVpiUQUkVXRJJuxBVdY4wLeDtwd/yYtTZora2PPd4ClAFLiVZwZ/e4fDZQEXtcDszpcc8cBpgqba39hbV2g7V2Q1FR0UiHLiIiIiITQH1sD93CBCq62VqjKyLDMJqpy5cAe6y13VOSjTFFxhhn7PFCok2nDlprK4FWY8yZsfW31wN/jl32IHBD7PE7gSesdgIXERERmfJqW6N76CZS0c1Ic2GMKroikphEthf6PfAisMwYU26MuTH21LWc3ITqPGCbMeZ1oo2lPmqtjVdnPwb8CjhAtNL7cOz4rUCBMeYA8Gngc6N4PyIiIiIySQwn6DochkyPi5ZJUtF96WA977rlRfzByTFekalmyDW61tr3DHD8A/0cu5/odkP9nb8ZWN3P8QBwzVDjEBEREZHJ6XebjlDZFODfLlvW6/hwgi5AttdNyySo6Da1d/Ivf3iNqpYAO483c8ZC9VkVGW+j7bosIiIiIjKo3750lF8/f4hwpPfqtDp/NOgWZCQWdLO8rgm/Rtdayxf/tIPq1gAAB+vaUjwikelJQVdERERExkygK8z+6lbaO8Psq27t9Vxta5DcdDdprsQ+kkaD7sSu6P75tQr+uq2Sz7xxKWkuBwdr/akeksi0pKArIiIiImNmb1UroVgld+vRpl7PJbqHbly21z3hK7q/eu4gq2Zl87ELFrOgIIODtaroiqSCgq6IiIiIjJkdFc0ApDkdbD3a2Ou5Wn8w4fW5MDmmLje1d7GsJAunw7CwKENTl0VSREFXRERERMbMjuPN5PjcnLO4gNeONfV6rrY1mNAeunFZXveEn7rcFgyRGdvzd2FRBkcb2ukMRVI8KpHpR0FXRERERMbMjuMtrC7N5tS5eRyo9ffqmlw3gopuSyCEtXbok1OkLRgmwxMLuoWZhCOWow3tKR6VyPSjoCsiIiIiY6IzFGFvVSurS3NYNycXa2HbsehU5rZgiPbO8DCDrptwxNLRFR6rIY9KMBSmMxwh03OioguoIZVICijoioiIiMiY2FfdSmc4wupZOaydkwvQvU63ew/d4TSj8kUD5ERdp9sWjAbwjDQnAAuLMgFtMSSSCgq6IiIiIjImdhyPVm/XlOaQ43OzuDize51ubWwP3eFWdIEJu063LRgN4PGpyzk+N4WZaaroiqSAgq6IiIiIjIkdFc1keVzMzU8HYN2cXLYea8JaS12soju8ZlTRANkyQSu6/ljQjU9dhug63UOq6IqMOwVdERERERkT24+3sHJWNg6HAeDUubk0tHVytKF9RBXd7HjQ7ZgcFV2IrtPVXroi409BV0RERESSriscYXdlC2tKc7qPnb2oEKfD8PW/7aa6JYDDQH5GWsL3PDF1eYJXdL29g259WyfN7RMznItMVQq6IiIiIpJ0FU0ddIYiLJ2R1X1sQWEGX7hiBY/uquZ3m45SkOnBGav2JiJ7sgTdPlOXAcrqtE5XZDwp6IqIiIhI0sXDaK7P3ev4h86Zz1vXzqKpvWtY63PhxBrdydKMCnpuMaTpyyLjyTX0KSIiIiIiwxMPuj2n8QIYY/jW29dwoMbP0pLMYd0zPc2J02EmcEU3ur1QZtqJ9zwnPx2Xw6jzssg4U9AVERERkaRr62cab1yGx8WDnzwHh0l82jJEQ3Kmx0XLhK/oOruPuZ0OSrK9VLUEUjUskWlJQVdEREREkq6/9ao9uZ0jW0GX5XVN2IpuWzCEx+XA1ee95aa7aVIzKpFxpTW6IiIiIjIsoXCESMQOek5rPx2IkyHb656wa3T9wVC/wT4vPY3G9s4UjEhk+lLQFREREZFhueyHz/Czp8sGPccfq7pmedyDnjdcWV4XLRO0ousPhvoN9qroiow/BV0RERERGZajDe08s6920HPagiEcBrzu5H7czPK6J/TU5Yy0/iu6TaroiowrBV0RERERSVg4YukKW3YcbyY8yPTl+DReM8yGU0PJ9rom3dTl3HQ3zR1dQ073FpHkUdAVERERkYQFQ9EtdNo6wxyqG3jLnNZAiCxvcqctQ2zqcsfEDLptwXCvjstxuelpRCwTtlu0yFSkoCsiIiIiCQt0Rbofv36secDz2oKhfkPfaGV53fiDIaydeNXR6Hvub+pyNPA3ap2uyLhR0BURERGRhAW6wt2Ptx8fOOgONI13tLJ9LiI2WlGeaFoH6boMaJ2uyDhS0BURERGRhPUMuq+XNw14XmswROaYTF2O3nMirtNtGyDo5sQquuq8LDJ+FHRFREREJGHBUHTq8uw8H7sqWugKR/o9zx/oImsMKrpZse17Jlrn5UjE0t4ZHmDqcrSiq710RcaPgq6IiIiIJCxe0d04P59gKMK+6tZ+zxuoMdNoxSu6E60hVVtnNHj3P3VZa3RFxpuCroiIiIgkLN6MasP8fAC2lfe/Tje6Rndsui7DxKvotgWjPwDor6Kb7XVjjNboiownBV0RERERSVggtr3QshmZZHtd/QbdSMRGg653DJpRxSu6gS4CXeFea4ZTyR+MBu/+qtgOhyHH59YaXZFxpKArIiIiIgkLxiq6XreTU2bnsq2fhlTtsfCZOQZTl7Nj4fnrf9vN6i//g6t+8nzSX2Mk4kF3oE7TeelpWqMrMo4UdEVEREQkYcFYRdfrdrK6NIe9Va0nNaTyB+KhL/lTl/Mz0jhrYQHLSrJYMzuHfdUnv/5AdlW0cOkPnqbOH0z6uNq6K7r9B93cdFV0RcaTgq6IiIiIJCw+VdjjcjC/IJ1QxFLdEuh1jj8YDXRjMXXZ5XTw+5vP5Lc3ncG1p88hYjnp9Qeyo6KZfdV+nt1fm/RxqaIrMrEo6IqIiIhIwgI9pi7PyvUBUNHUO2jGG0WNxfZCPcVf/3hjR0LnxyvNmw42JH0sbUMEXVV0RcaXgq6IiIiIJCxe0e0ddHsHzcE6ECdTafz1mxMMurEw+tLB+qSPZcipy740dV0WGUcKuiIiIiKSsGAoVtF1OZiV6wXgeJ+g2z11eZwqun0rygOJh9HD9e1UNSd2TaL8wXgDroGmLrtp6wzTGUpsPbGIjI6CroiIiIgkLNAVxuUwuJwO0tNc5KW7Twq63VOXx2CNbk9et5OCjDTKE5y63Bo8sffupkPJrer6g104DHjd/X+8zs1IA7SXrsh4UdAVERERkYQFuiJ4XCc+Qs7K9Z00dXmoxkzJVJp38usPxB8IMSffR5bHxUtJXqfbFgyT4XFhjOn3+bz0aAfqpg6t0xUZD2P/3UdEREREpoxAKIzXfWJ/3Fm5Po7Ut/U6Z6j1qsk0K8dHWa0/oXP9wRA5PjdLirPYlOR1uv5gaNDmW7m+aEW3sU0VXZHxoIquiIiIiCQs2BXpFXRLc30cb+zAWtt9rDUYIs3lIM019h81Z+X6ON7U+/UH4g+EyPS4OGNBPgfr2qhJcFuiRLQFQ4MG+9xYRbdRnZdFxoWCroiIiIgkLBAK4+mxDrU010dbZ5iWwIn1r/7A4NXNZJqV66W9M0xzAlOCW4MhMj1uzlxYAMCmQ8mbvuwfIujmaY2uyLhS0BURERGRhAW7wnhcvacuQ+8thoaqbibT7LzYXroJrNNtC4bI8rpYNSubjDQnmw8nL+i2BUODrknWGl2R8aWgKyIiIiIJC3RFenUWjm8x1DPo+ocIfckUD9rHE+i8HB+Xy+lgdl46lUncYiha0XUO+LzP7STN6aBRFV2RcaGgKyIiIiIJC3SF8bp6r9GF3kG3NRAic4y3Forrr6I8EH/gRKU5PyON+iQ2hop3XR6IMYbcdDdNbaroiowHBV0RERERSVgw1LuiW5jpwe00HG86UR0dqgNxMhVkpOFxOagYojobDIXpDEe69/YtyEyjIYlBN5Eqdl56miq6IuNEQVdEREREEhbo6r29kMNhmJnjS9kaXWNMd+fnwfgDvff2LchIo84fTMoYrLVDrtGFaOdlrdEVGR8KuiIiIiKSsEAojKfPtkGzcr0nr9Edp6nL0df3dTejevVoIy+U1Z10jj/YJ+hmemgNhOgMRUb9+sFQhFDEDhnuc9Pd6rosMk4UdEVEREQkYYE+++hCNGj2XaM7XlOXIbpOuKKpg6b2Tm66fTNf/cuuk87pDrreE2t0gaRMX+4bogcSnbqsiq7IeFDQFREREZGEBftMXYZo0KxqCRAKR+gKRwiGIuM2dRmiQbumNcg3H9pDQ1tnv+tg41OX4wG8MDMadOvbRj99uS0WdIeu6KbR1N6JtXbUrykig1PQFREREZGEBUIRPO6+U5d9RCxUtwa7Q994bS8Uff3oFkd3bz6G1+2gqZ+qqb9PGM3P8ABQ709mRXfg7YUgui64K2xp1jpdkTGnoCsiIiIiCYlELJ2hCB7XyVOXIbrFT2ug9xTh8VCaF339wsw0PnjOAoKhCB2d4V7n9J26XJCZxKnLgcQquouLMwHYW9U66tcUkcEp6IqIiIhIQoKxxk3ePhXd0lhFtaKpoztQjuca3SXFWWSkOfnSW1YyNz8dgKaO3gG2tc/U5YKM+NTl0QVday2/fPYQaS4Hi4oyBz13xcxsAHZXtozqNUVkaEMGXWPMr40xNcaYHT2O/Zcx5rgx5rXY1xU9nvu8MeaAMWavMeayHsfXG2O2x577kTHGxI57jDF3x45vMsbMT/J7FBEREZEkCHRFq6Tefiq6DgO7K1sTXq+aTEVZHl7/8qVcua6UvHQ3AI1tvacH963oZnvduByG+lFuMXTP5mM8truaz162rLuyPZCSbA956W52V56o6D68vZJP3/PaqMYgIidLpKJ7G3B5P8d/YK1dF/t6CMAYsxK4FlgVu+anxpj4d8KfATcDS2Jf8XveCDRaaxcDPwC+PcL3IiIiIiJj6ERFt3fQTU9zce6SIh587TgtgWjAHM+pywAuZ/RjbY4vWqntW9FtC4ZwGPDFxu5wGPIy0kY1dflofTtf/csuzlpYwIfOWTDk+cYYVszMZnfViYruXS8f5U9bj6tBlUiSDRl0rbXPAA0J3u9K4A/W2qC19hBwANhojJkJZFtrX7TR/4rvAK7qcc3tscf3ARfHq70iIiIiMnF0V3TdJ3+EfOf62VQ0B3h0Vw0wvlOXe8qNVXSb+zSkag2EyPS46PkxsyAjjboRNKNqDXRxy9NlvOOWF3A4DN9911ocjsQ+vq6Ymc3eqtbuDtVbjjQSsdDRFR76YhFJ2Gi+A33SGHM9sBn4jLW2ESgFXupxTnnsWFfscd/jxH49BmCtDRljmoEC4OSdvkVEREQkZQKhaBjr24wK4I0rS8jyunhga/Qj33hXdOPy0qMV3b771fqDoZM6QRdkptEwzO2Fmto7ueT7z1DnD/KGxYX822XLKB1iynJPK2dmEwxFOFzfRksgRHusaZY/ECI9LTV/ZiJT0UibUf0MWASsAyqB78WO9/ejLDvI8cGuOYkx5mZjzGZjzOba2tphDVhERERERifQ1X8zqugxJ285ZVb3OeO5RreneEW379RlfyB0UvguyPAMuxnV/ho/df4g37tmLb+96QzWzckd1vXxhlS7KlvZdPDEpMnW2BpiEUmOEQVda221tTZsrY0AvwQ2xp4qB+b0OHU2UBE7Pruf472uMca4gBwGmCptrf2FtXaDtXZDUVHRSIYuIiIiIiMU7J663P9+se9cX9r9OCNF1Umv29nvXrr9VXTzM9JoGObU5XjzquUzs0Y0vsXFmbidht2VLWw6VN99PN4VWkSSY0RBN7bmNu5qIN6R+UHg2lgn5QVEm069bK2tBFqNMWfG1t9eD/y5xzU3xB6/E3jCajW+iIiIyIQTGGB7objT5uaxoDCDjDQnzgTXrI6FXF8aTe19thcKhsj0unsdK8xMozUYIhhKfH1sfE1vQYZnRGOLb0O043gzmw83siS2t65fQVckqYb8UZsx5vfABUChMaYc+DJwgTFmHdEpxoeBjwBYa3caY+4BdgEh4BPW2vh3jo8R7eDsAx6OfQHcCtxpjDlAtJJ7bRLel4iIiIgkWbwZVX9rdCHaVfhfLlnC5sON4zmsk+Smu0+q6LYFQ8zus5Y2PxZWG9o6mZmT2DrbeJfm/Ng+vCOxcmY2f369gnDEcvGKEvbX+PEHu4a+UEQSNmTQtda+p5/Dtw5y/jeAb/RzfDOwup/jAeCaocYhIiIiIqk1WNfluCvXlXLlutIBnx8P/QVdfyBEhqd3QC/IjIbVen/iQbfeHyTb6yLNNdJWN9F1un/cehyAS1YUc8vTZZq6LJJkI/8vVERERESmlfg+ugNVdCeKXF/ayc2ogiEyPb2nLhfEqrLDaUhV19ZJYebIpi3HxRtSLSjMYFFRZvf4RCR5FHRFREREJCFDNaOaKPIy3L22F4pEbDTo9u26HAus8QZTiaj3B0c1bRlgRayR1RkL8ru7U6uiK5Jc2qxLRERERBIy2PZCE0mOL43m9i6stRhjaOuMhsisfrouw4l1t52hCG6nIdo7tX8NbZ0sKMwY1fgKMj187cpVnL24kDSXA4/LoYquSJJN7O9SIiIiIjJhDNWMaqLITXfTGY7QERtvPET2rehme124nYb6tk7aO0O84dtPcPsLhwe9d72/s7sSPBrvP2t+97TlLK9bFV2RJFPQFREREZGEBEJhHAbcztRtHZSIvPToWtz49OW2eNDtU9E1xpCfkUa9P8jftlVS0xqkrLZtwPuGI5aG9k4KRzl1ua8sr0sVXZEkU9AVERERkYQEuyJ43c5Bp/ZOBDm+aBCN76Ubr5b2DboQ3Q+3oa2Tu185Fr2mY+BtfhrbO7GWpFR0e8r0uPAHtL2QSDIp6IqIiIhIQgKh8IRvRAUnKrrxLYYGmroM0S2GXjvWxOYjjbFrBu7AnIw9dPuT6XH1O3W5vTPE5/+4ndrWxJtliUiUgq6IiIiIJCTQFcEziv1jx0tueryiGwu6g1Z006jzd+JyGNaU5py0/25PdbHuzPH9d5Mlc4Cpy5sONfD7l4/y+O7qpL6eyHQw8b9TiYiIiMiEEOiaHBXd3HhFN7aXbusAa3QB8jOi05AvWVHC4uLMk/bf7aneH31utPvo9pXl7b+iu6+qFYCyWn9SX09kOlDQFREREZGEBEOTo6Kb4+szdTkWIrMGmLoMcO3GOeT43INWdOP77RYkuxmVp/+K7t7qeNAduEGWiPRP++iKiIiISEImS0XX63biczu719vGuy5n9FPRvWLNTAJdYc5dUsRrx5poDYQIhSO4nCcH+oa2Tow5MTU6WeJTl+P7/sbtVUVXZMQm/o/kRERERGRCiHZdnhwfH/PS3d3bC/mDITwuB+5+wuuCwgw+c+kynA5DbqwS3DxA5+W6tk7y09NwOpLbdTrT4yYcsd37/kJ0K6P9NX5cDsOxhvbuPYxFJDGT4zuViIiIiKRcIBTG45r4FV2AnPS07mnIrcFQv9OW++puYjVA0K33B5PeiApOdIP291ine6S+jc5QhLMXFxKxcLhe05dFhkNBV0REREQSEp26PDk+Pub63DTHGkv5A6F+G1GddE2fbYn6amjrpCAjuY2oALJjQbe1xzrdfbH1uVesngFAWY2CrshwTI7vVCIiIiKScsFQZFKs0QXIy+g9dbm/PXT7ild04wHZWsuPHt/PsYZ2INp1eUwqup6TK7p7qloxBi5dFQu6WqcrMiwKuiIiIiKSkEBXGO9kmbrsS+vVdTmhim5sjW5jW/S6400dfP/Rffz6+UNAdB/dZHdchh5Bt09Fd15+OvkZaZTm+hR0RYZJQVdEREREEhLoiuCZJFOX89LdNLV3Ut7YzrbjTczLzxjymhP770aDblVzAICn9tbSGYrQEghRkOQ9dOHEGt3WwIkp03urWllakgXA4uJMBV2RYZoc36lEREREJOUmy/ZCEA2toYjl83/cDsCnLlky5DXZXjfGQHNsW6KqlmjQPVTXxtajjQBjMnU5yxMN2K2xqcuBrjCH69tZNiMadBcVZVJW00YkYpP+2iJTlYKuiIiIiAzJWhtdo+uaHB8fc33RQPrs/jo+eeFiSnN9Q17jcBhyfO6TKroA979aDjAmzajiHaHjU5fLav2EI7a7oruoOIOOrjCVLQFePdrIZT94hprWwID3ExEFXRERERFJQDAUAcAziSq6APML0vnweQsTv87n7l7bW9UcwOd2sqAwg79tqwSgcAwquhl9mlHFOy4v71HRBdhd0cJn79vG3upWDte1J30cIlOJgq6IiIiIDCnYFQ26k2Xq8sKiDNJcDr5y5eph7f2bk55GY4+pyzNyvFywrIi2zjAA+WPQjCrN5cDjcnRXdPdW+XE7DfMLo+uKFxdHg+5X/7qLAzXRtbodXeGkj0NkKlHQFREREZEhBULRYOWZJFOXFxdnsfMrl3H+0qJhXRfdf/dERbck28OFy4q7nx+LZlQQnb7cEqvo7q9uZWFhJm5n9M+6ICONHJ+bow3t3VXegIKuyKAmx3cqEREREUmpeLCaLBVdoDsoDke0W3Ms6LYEmJnjY+OCfHxuJ26nITuB/XhHItPj6q7o7qtpZUlJZvdzxhiWlmSSm+7mq1euBhR0RYYyNv+lioiIiMiUEl+j650k2wuNVG56Gk3tnUQilpqWICXZXrxuJ+csLmB3ZSvGmDF53SyvG3+gi/bOEOWNHbzztDm9nv/vq9fQFbbkxNYex6eSi0j/FHRFREREZEjdFd1hrHedjHJ8bloCIer8QTrDEWZkR6cqf+2q1dT7O8fsdeMV3YO1bVhLr4ouwJJYB+Z6fxA4MZVcRPqnoCsiIiIiQwp0xbsuT/WKbrRiujfW+XhGjheAmTk+ZuYMvUXRSGV6XRxraGd/TfR1l/YJunHxqeOauiwyuKn9nUpEREREkmIyrtEdiXjQ3VMZD7pjF257yvK4aA2E2F/tx+UwzCvI6Pe8+J9/R6emLosMRkFXRERERIbUvUZ3ik9dzk2Pbh+0pyoWdLO94/K6md7o1OX9NX4WFGYM2EjL6TC4nUZTl0WGoKArIiIiIkM6UdGd2h8fc33xqcstOAwUZiZ/39z+ZMWDbnXrSetz+/K6nJq6LDKEqf2dSkRERESSYvpMXY4G233VfoqzvLhGsEXRSGR63IQjlsP17Swuzhr0XG+as3vNtIj0T0FXRERERIbUMV2Cbqyi2xmKUJIzPtOWITp1OW6gRlRxXreDoCq6IoNS0BURERGRIbUGQkB0iu1Ulu1zE98qN7610HjI8pz4c10yVEXX5dQaXZEhKOiKiIiIyJBaOrrwuBxTvqLrdBiyvdGq7lhuJ9RXZizoOh2G+YXpg57rdTvp6FTQFRmMgq6IiIiIDKkl0EVWLABOdfEthkrGqeMynKiUzytIxzNEZ2uv26E1uiJDUNAVERERkSG1BEJk+6b2tOW4+DrdGTnjN3U5vkZ3SfHg63MhWtHV1GWRwSnoioiIiMiQWjqmT0U3J9Z5eUb2+E1dzvJE/2yHWp8LsaCriq7IoBR0RURERGRIrYEQ2VO8EVVcXnq8ojt+U5dn5Hi5YFkRl62aMeS5XrdTXZdFhjA9vluJiIiIyKi0BLoozRu/CmcqdU9dHsc1umkuB7d9cGNC53pdju59jUWkfwq6IiIiIjKklo7pU9G9eEUJneEIvrSJ2WHa63Z272ssIv2bHt+tRERERGRUWgNd3dvuTHXnLS3ivKVFqR7GgNR1WWRoWqMrIiIiIoMKdIUJhiLdW+BIasW7LltrUz0UkQlLQVdEREREBtUaCAGQ7ZseFd2Jzut2Yi10hlXVFRmIgq6IiIiIDKo10AUwbaYuT3Red3TtsKYviwxMQVdEREREBtUSq+hq6vLE4HVHP8InusXQsYZ2giE1r5LpRUFXRERERAbVXdHV1OUJweuKVnQT6bzcGYpw2Q+f4a5NR8d6WCITioKuiIiIiAyqpSO2RldTlyeE4UxdburopL0zzPHGjrEelsiEoqArIiIiIoNqiVV0NXV5YohPXQ4kUNFt6Yj+3TXFfhWZLhR0RURERGRQmro8sfi6K7pDB93meNBtV9CV6UVBV0REREQG1dIRwmEgI82Z6qEI4IkH3dDQU5fjQbe5o3NMxyQy0SjoioiIiMigWgJdZHndGGNSPRThxNTljk5VdEUGoqArIiIiIoNqDYTI9ml97kQRb0aVyJZBze1aoyvTk4KuiIiIiAyqpaOLLI/W504U3mGt0Y12zG5u78JaO6bjEplIhgy6xphfG2NqjDE7ehz7H2PMHmPMNmPMA8aY3Njx+caYDmPMa7GvW3pcs94Ys90Yc8AY8yMTm/tijPEYY+6OHd9kjJmf/LcpIiIiIiOliu7E4nXFuy4nvka3MxxJaN9dkakikYrubcDlfY49Cqy21p4C7AM+3+O5MmvtutjXR3sc/xlwM7Ak9hW/541Ao7V2MfAD4NvDfhciIiIiMmZaAl3aQ3cC8aUNv+syaJ2uTC9DBl1r7TNAQ59jj1hrQ7HfvgTMHuwexpiZQLa19kUbnTNxB3BV7Okrgdtjj+8DLjbqdCAiIiIyYbR0RJtRycTgdcWDbuIVXVDQleklGWt0PwQ83OP3C4wxW40xTxtjzo0dKwXKe5xTHjsWf+4YQCw8NwMF/b2QMeZmY8xmY8zm2traJAxdRERERIaiqcsTi8NhSHM6EpqK3NLRhdMRrSE1aYshmUZGFXSNMf8JhIDfxQ5VAnOttacCnwbuMsZkA/1VaOOr4Qd7rvdBa39hrd1grd1QVFQ0mqGLiIiISALCEUtrMKSK7gTjcTsSnrpcmuuLPlZFV6aREQddY8wNwFuA98amI2OtDVpr62OPtwBlwFKiFdye05tnAxWxx+XAnNg9XUAOfaZKi4iIiEhq+APR1WrZXlV0JxKv25nY9kIdXcwrSAe0xZBMLyMKusaYy4H/AN5mrW3vcbzIGOOMPV5ItOnUQWttJdBqjDkztv72euDPscseBG6IPX4n8IRV73MRERGRCaElEA1H2T5VdCcSr9uR8BrdufmxoKuKrkwjQ/5ozhjze+ACoNAYUw58mWiXZQ/waKxv1EuxDsvnAV81xoSAMPBRa228Ovsxoh2cfUTX9MbX9d4K3GmMOUC0knttUt6ZiIiIiIxad9BVRXdC8bqcQ05d7gxFtxSake0lzeXQGl2ZVob8jmWtfU8/h28d4Nz7gfsHeG4zsLqf4wHgmqHGISIiIiLjr7V76rIquhOJL23ooBvvuJyT7ibX59YaXZlWktF1WURERESmqJYOTV2eiLwu55Bdl7uDrs9Nbrq711ZDIlOdgq6IiIiIDKglVtHN0tTlCcWTwBrd5h4/pMjxubVGV6YVBV0RERERGVBr9xpdVXQnEq976KnLLT0qujm+NHVdlmlFQVdEREREBtTSEa3oZqqiO6FEtxdKrKLbPXW5Xc2oZPpQ0BURERGRAbUGukhPc+J26mPjROJ1ORJvRuWLNqNSRVemE33HEhEREZEBtQS6NG15AhpW1+VYRbe9M0wwNPg1IlOFgq6IiIiIDKilI6RGVBOQ151Y1+V4NT4nPa37mMh0oKArIiIiIgNqDXZpa6EJKDp1OYK1dsBzmju6yIn93eXGftVeujJdKOiKiIiIyIBaOkJkq6I74XjcToBBG1L1Crrp0V+1TlemCwVdEREREelXKBzhWGM7BZmeVA9F+vDGg+4ge+k2d5yoxuf6olOXtZeuTBcKuiIiIiLSrxfK6mlq7+KSFSWpHor04XVHP8YHBmku1dJfRVdbDMk0oaArIiIiIv168PUKsjwuLlhWlOqhSB++WEV3sM7LPacu58SC7mibUR1v6uCHj+0jEhl4bbDIRKCgKyIiIiInCYbC/GNHFZeumtE9TVYmjvjfyWCdl3sG3SyPC6fDjHrq8vcf2ccPH9vPnqrWUd1HZKwp6IqIiIjISZ7aW0trMMRb185M9VCkH91TlwdYo9sVjtDeGe4OusYYcnxumjpGPnW5oa2Tv2yrAGB3ZcuI7yMyHhR0RUREROQkf3m9gvyMNM5ZXJjqoUg/vK7Bpy7Hpyjn9NgaKtfnHlVF9+5XjtEZiuB0GAVdmfAUdEVERESkl7ZgiMd2V/Om1TNwO/VxcSLyDLFGt7+gm5PuHvEa3XDE8tuXjnDWwgJWzsxmd5WC7liIRCz3vHKMxjY1DRstfecSERERkV7+sbOKQFeEt66dleqhyACGmrqc7Iru47urOd7UwQ1nz2PFzCx2V7ZirRpSJdvdm4/x2fu38cDW46keyqSnoCsiIiIivfzh5WPMK0hn4/z8VA9FBhDvuhwcYHuheNDN7hl009NGvEb3zpeOMDPHyyUrSlgxM5uGtk5qWoMjupf0r94f5FsP7wGgvLEjxaOZ/BR0RURERKTbgRo/Lx9u4NrT5+JwmFQPRwbQ3XW5s/+g29JfRTfdTYN/+EE3HLG8criBy1fPwOV0sGJmNgC7tE43qb758B7agiHyM9I43tSe6uFMegq6IiIiItLt7leO4nIY3rl+dqqHIoPwjmCNbkm2l7bOMP5gaFivdbi+jUBXhJWxgLtiRvRXNaRKnhfL6rlvSzkfPm8hp8zOUUU3CRR0RURERASIToO9/9XjXLKihKIsT6qHI4PoXqMbOnmN7rbyJn7xzEGyvK5eQXdGtheAqubAsF4rHmjjldycdDeluT52V07NvXTv31LOkfq2cXu9Hceb+ehvtzCvIJ1PXbSE2Xk+jjcp6I6Wgq6IiIiIAPDIzmoa2jq5duOcVA9FhjDQ9kJ3v3KUd/7sRSIRy+0f2kia68TH/ZJY0K1uGX7QdToMi4szu49FG1JNvYpuWa2fz9z7One8eGRcXm93ZQvvu3UTmR4Xv73xDHxpTkpz02lq76JtmJV36U1BV0REREQA+MMrRynN9XHukqJUD0WG4HAY0pyOXl2XK5o6+MIDO9i4IJ+/fepcTpub1+uaGTkjq+juqWxlUVFG93RpiFZ3D9b6B5w6PVn9Kdbt+Pg4TB0OdIW5/tcv43M7uevDZzAnPx2A0jxfdAyq6o6Kgq6IiIiIcKS+jecP1PPu0+fgVBOqScHrdvQKmre/eBiAb71jDXkZaSed3z11uU9FtzMU4RfPlHHed57kF8+UEY703jZod2VL97TluBUzs4lY2F/tT8ZbmRAiEdu9rU9F89iHzEd2VVPbGuS716xlXkFG9/HS3GjQLW9UQ6rRUNAVEREREe5+5RgOA9dsUBOqycLrdnYH3bZgiLs2HeXy1TOYnZfe7/m+NCfZXlevqcvby5u5/IfP8N8P7cHpMPz3Q3u45pYXOFwXXaPa1N5JRXOg36ALU6sh1eYjjZQ3dpCX7qZiHKqp920ppzTXx1kLC3odnx2v6Koh1ago6IqIiIhMc13hCPduKefCZcXMzPGlejiSIK/bSWsguo7z3s3HaA2EuOkNCwa9ZkaOt9fU5e8/upfmji5+88HTeeIz5/PDd6+jrLaNj/52C9ba7oZTy2dk9brPvPx0fG4n+6qnTkOqB7aW43M7effpc6nzd47ptOyq5gDP7a/lHaeVnrSNV1GmhzSng3JNXR4VV6oHICIiIiKp9cSeGmpbg1y7cW6qhyLDsGJmFn/bXonn7tfYfKSR0+bmcmqfdbl9lWR7e1V0D9a1cdaiAi5cVgzAVaeWEgyF+Y/7t/PK4cbuiu3KPhVdh8NEQ/MwG1tNVIGuMH/dVsnlq2ewJNZ0q6Kpg4VFmUNcOTJ/3FpOxMI7+tnGy+EwzMr1qqI7SqroioiIiExzv3/5KCXZHi5cpiZUk8n/Xnsqn7poMX/ZVsHRhnZuOnfhkNfMyD4RToOhMMca2llYmNHrnLetLSXb6+LOl46wp6qFgoy0frebKsryUNMaTM6bSbGn9tbQGghx9aml3c2gKprGJsRba7lvSzmnz8/rtTa3p1JtMTRqquiKiIiITGPHGtp5el8tn7xwMS6naiCTidft5NOXLuMta2fxwoE6Lls1Y8hrZuR4qW0NEgpHONbQTsTCgqLeYcuX5uSaDXO4/YXDzMz1smJmNsac3KCsOMvDzoqpsUb31aNNpLkcnL2ogMrY1O6xWqf71L5aDta28ZHzBv7BRGmujyf31o7J608X+m4mIiIiMo394NF9pDkdXHeGpi1PVktLsvjAOQsS6pZdku0lYqHO38nB2mjDqQWFJ0/Pfe8ZcwlFLMcaOlgxM+uk5+P3Gu6evBPV/upWFhVl4nI6KMn2YgxJXyO79Wgj7791Ex/8zSsUZXm4Ys3MAc8tzU2ntjU45bZvGk8KuiIiIiLT1K6KFh547TgfOGe+mlBNEz23GDpYFw+6J0+fXViUyblLCgFYPiP7pOchWtFt7wzjD4bGaLTjZ1+1n6Ul0cCf5nJQkuVNakXXWstNt29md2ULn718GY/96/lked0Dnh+fPl05zD2P5QQFXREREZFp6tt/30O2183Hz1+c6qHIOJmREwu6zQEO1bZRmJlGjq//wHXTuQtJczpYP6//BlfF2dF1uzWTvKrbFgxxvKmDpSUnKtezcpMbdGtbg9S3dfJPFy3h4xcsJid94JALJ/bSVUOqkVPQFREREZmGXjhQx9P7avnEhYuG/NAtU0dJrKJb3RLgUF1bv9XcuPOXFrHtvy5l/gDnFGdF7zXZG1Ltr/EDsLj4xBTuWbm+pAbdA7HXWJRgF+f4Xrrlje1JG8N0o6ArIiIiMg39btNRirI8XH/W/FQPRcZRQUYabqeJTV32s7Cf9bk9ed3OAZ8riVV0J9s63UjEdm+bBNH1uUCvim5pno+KpgCRiE3Ka5bVnhymBzMjx4vDoM7Lo6CgKyIiIjINldX6WVOaM2iQkanH4TAUZ3nZX+2nzt95Usfl4SiKVXRrJ1lF9+87q3jT/z7LjuPNQLSi63E5mJuf3n1Oaa6PznCEurbkvLcDNX4yPa7uHw4Mxe10MCNbe+mOhoKuiIiIyDRjreVoQ3uvD/YyfczI8bLpUD3QfyOqRGV7XXhcjkk3dXlPVbSC+8iuagD2xTou9+xaPStndHvp7q5s4Wj9iWnHB2r9LCrK6HebpoGU5vmS3vl5OlHQFREREZlm6vydtHeGmV+goDsdzcj20hqIdkpeOIqga4yhONsz6ZpRHamPdpt+Yk806O6v9rOkpPeU4njX45FWVD98x2b+4/5t3b8vq2ljUYLTluPm5KX3CssyPAq6IiIiItNM/IP+vIKRhxyZvOINqRwG5o7yhx0lWV6qWyZXRfdwLDzuON7CgRr/SR2XIdqMChhRQ6ryxnbKGzvYcqSRQFeY1kAXVS2BhBtRxS0syqCqJTAltm9KBQVdERERkWnmSOyD/mhDjkxOM3Ki60Rn56XjcY1ujXZxtoea1slV0T1c18bGBfkA/OKZMgCW9Km2ZntdZHpcI2oGtelgAwCd4QhbjjRysDb6g6VEG1HFxc8/FLtehkdBV0RERGSaOdLQjjEntjCR6SVe0R3N+ty44izvpFqj29TeSXNHF29cUcKcfB8PbD0OcFJF1xgz4r10Nx2qJ8vrwuUwvFBWN+ytheLi58c7NsvwKOiKiIiITDNH69uYleMbdTVPJqcZSQy6RVkeWgMhOjrDo77XeIhPW55fmMHFy0voCls8Lgdz+mnMVprrG1FF9+VDDZy5sIC1c3J5oayeA7V+XA7DvGHOoJhbkI7TYRR0R0hBV0RERGSaOdLQPuwP3TJ1zI6Fur5VzJGIV4cny/Tlw3XRacALCtO5eEUxwEkdl+NmjSDoVrcEOFzfzhkL8jl7UQHbypt5/VgT8wszcDuHF708Lidz89O7K8IyPAq6IiIiItPMkXoF3emsNNfHXR8+g3esLx31vYqzout9J8v05cP1bbFp++mcsaCALK+L5TP7D/zzCzJoau+isa0z4ftvOhRdn3vGggLOWlRAOGJ5oayeRSPcr3hRUaYquiPkSvUARERERGT8tAa6aGjrZG6+Oi5PZ2cvKkzKfYqzY0F3knRePlLfzqwcH153dNr+H24+k6JMT7/nxrcc2lfdyhkLCxK6/6aD9WR6XKyYmUUoYklzOegMRYbdiCpuUXEGz+yrJRSO4BpmRXi605+WiIiIyDQS77isPXQlGYqzJtfU5UN1bcwvPPFvf9WsHIpj06/7ik/t3lfdmvD9Xz7UwIb5ebicDrxuJ+vn5gHDb0QVt6gok85whPIR7uc7nSnoioiIiEwjRxu0tZAkT166G7fTTJq9dI/UtyW8f/TMHC9ZHhf7qhObOlzvD7K/xt+9dRHA2YuileCRVnTj12md7vBp6rKIiIjINBKv6Cb6YV9kMMaY2BZDE7+i29zeRWN7V8KzGYwxLCnJTLii+9qxJgBOn38i6L7njLkYE60cj8SiwhNbDF1CyYjuMV2poisiIiIyjRypb6MgI41Mj+odkhxFWR5qJ0EzqsP10Y7L84fxQ56lJVnsT7CaGm8ataRH9bYw08MnL1rSb1fnROSkuynM9Kgh1Qgo6IqIiIhMI+q4LMlWnOWZFM2ouoPuMPYPXlKSRUNbJ3X+od9fWU0bhZlp5KanjXiM/VlcnEFZbVtS7zkdKOiKiIiITCNHG9o1bVmSqiTbS1VLgEjEpnoogzpcF1ufnp/4D3qW9ui8PJSyWj8LR9h0ajCLijI5UOPH2on95zvRKOiKiIiITBPBUJiK5o5hfdAXGcrKWdk0d3Tx9p+90L1OdSI6Ut/GrBxv99ZCiYh3Xt4fa0h150tH+M8Htvd7blmtf8TdlQezqCiT5o4u6oexn68kEHSNMb82xtQYY3b0OJZvjHnUGLM/9mtej+c+b4w5YIzZa4y5rMfx9caY7bHnfmSMMbHjHmPM3bHjm4wx85P8HkVEREQE2Hy4EWthxcysVA9FppB3b5jD965Zy/GmDq76yfM8vrs61UM6SSgc4fXypmHPZijO8pDtdbG3upX2zhDf/cde/vDKMdo7Q73Oa2jrpLG9i0VFyZ8toc7LI5NIRfc24PI+xz4HPG6tXQI8Hvs9xpiVwLXAqtg1PzXGxH9k8jPgZmBJ7Ct+zxuBRmvtYuAHwLdH+mZEREREZGD3bj5GttfFBcuKUz0UmUIcDsM71s/myX+7gDSng5cPN6R6SCf5+TMHKatt471nzh3WdcaYaEOq6lb++Opxmju6CEcs28ube513MNYsatEItxEazMJYeD5Up3W6wzFk0LXWPgP0/dd6JXB77PHtwFU9jv/BWhu01h4CDgAbjTEzgWxr7Ys2Orn8jj7XxO91H3BxvNorIiIiIsnREuji4R1VvG3drGFN3RRJVKbHFe3APMEaU+2ubOGHj+3jzWtm8pZTZg37+iUlWeyr9vPr5w91h86tfaZox7six7cDSqZZOT7SXA4OK+gOy0jX6JZYaysBYr/GfyxYChzrcV557Fhp7HHf472usdaGgGagYITjEhEREZF+/PX1SoKhCNesn5PqocgUVpjloWYCbTXUFY7wmXteJ8fn5mtXrR7RPZaVRNfIHqxt41MXLWF+QTpbjzb2Oqesto00l4PSPF8yht2Lw2GYX5DOQQXdYUl2M6r+KrF2kOODXXPyzY252Riz2Rizuba2doRDFBEREZn6QrEP+He+eBhrLfduOcbSkkxOmZ2T6qHJFFY8wfbUfbGsnl2VLfy/t64iP2Nk2/7EG1KVZHu4Ys1MTp2bx9ajTb26IJfV+FlYmDHi/XKHsqAwQ1OXh2mkQbc6Nh2Z2K81sePlQM8fE84GKmLHZ/dzvNc1xhgXkMPJU6UBsNb+wlq7wVq7oaioaIRDFxEREZn6Ht1Vzf2vlvOlP+/kul9uYuvRJq5ZPwetEJOxVJzloaY1kOphdItvC/SGxYUjvsfymdmkOR188JwFpLkcnDo3l5rWIJXNJ97nWHVcjptfmMHR+nbCE3wLp4lkpEH3QeCG2OMbgD/3OH5trJPyAqJNp16OTW9uNcacGVt/e32fa+L3eifwhNUmUSIiIiKj8pvnDzM7z8eX3rKSLUcacToMV51aOvSFIqNQnOWlsb2LzlAk1UMBolOK89LdI67mAuRnpPHUv1/AzecuBODUOdENZ7YebQKi23YdbWgfk47LcQsLM+gMR6ho6hiz15hqXEOdYIz5PXABUGiMKQe+DHwLuMcYcyNwFLgGwFq70xhzD7ALCAGfsNaGY7f6GNEOzj7g4dgXwK3AncaYA0Qrudcm5Z2JiIiITFM7jjfz8uEG/vOKFdz4hgWcu6SQ6pYARVmeVA9Nprji7Oi/sVp/kNLc5K9XHa6yWn/39jyjMavHe1k+MwuPy8HWo428+ZSZHKlvJ2LHpuNy3IJYk6uDdW3M0T7YCRky6Fpr3zPAUxcPcP43gG/0c3wzcNIKcGttgFhQFhEREZHRu+2Fw6SnOXnX6dEVZUtLsrrXGYqMpeLYD1NqWgITI+jW+HnjypKk3tPtdHDK7Jzuzstlsf1tx3bqcjTcHq5r4/yl/S/htNbS3NFFbvrIq9dTSbKbUYmIiIhICtX5gzz4WgXvOG02OT53qocj00xxlhdgQnRebmzrpL6tMykV3b5OnZvH9uPNdIYi3d2QFxSO3dTlokwPmR7XoA2pHtlVzRn//fiEWiOdSgq6IiIiIlPIA68epzMc4Yaz56d6KDINxacuT4Sg27237RhUWk+dk0tnKMIn73qV+18tZ2aOlwzPkJNlR8wYw4LCjEG3GNpf3UowFGHn8ZYxG8dkoqArIiIiMoW8dLCehUUZY1LFEhlKQUYaxkBtS+qrivGgOxb/LZy1qIBTZuewu6qFQGeYt66dlfTX6Gt+YQaH6vwDPl/dEv3hwp6q1jEfy2Qwdj92EBEREZFxFYlYthxt5LKVM1I9FJmmXE4HBRmeCVLRbcPjcvRqJJUsuelpPPjJNyT9voNZUJjB37ZVEAyF8bicJz0fn7K8t0oVXVBFV0RERGTKKKv109TexYb5eakeikxj0b10Ux90D9T4WVCYgdMxNfaOXliYQcTCsYb2fp9XRbc3BV0RERGRKeKVw40AnD4/P8UjkemsONszIRoiJWtroYlifqzZ1cHa/tfp1sSmi5fV+ukKT4x9jFNJQVdERERkith8uIHCTA/zCrTPpqROcZaHmpbUVnQDXWGONbSP6ZY/421BQTToHq4/OehGIpZaf5CZOV66wnbQ7szThYKuiIiIyBTxypEGNszLw5ipMVVTJqfiLC91/iDhiE3ZGA7XtxGxY9OIKlVy0t0UZKT1G2Ib2zvpClvOWxLdY1fTlxV0RURERKaE6pYAxxo6tD5XUq4420PEQn1b6qq6B2rGbmuhVFpQmMHefkJsfE302YsLcDqMGlKhoCsiIiIyJWzW+lyZIIqzonvp1qawIVVZTRvGwMKijJSNYSyctaiA14410dTe2et4dWx97uw8HwsHCMPTjYKuiIiIyBTwyuEGfG4nK2dlp3ooMs0VZXkBUtp5uazWz+w8H173ydvwTGYXLS8mYuHpfbW9jsfXRBdneVk2I0tTl1HQFREREZkSNh9p4NS5ubid+ngnqdVd0U1hQ6rD9W0sKJxa05YB1s7OpSAjjcd31/Q6Hu9yXZTlYfmMLMobO/AHQ6kY4oSh74QiIiIik1xnKMKeylbWzclN9VBEKIoF3VRuMXS4ro15+VOv+7jDYbhweTFP7a0h1GMLoeqWILnpbrxuJ8tmRGd17Kue3lVdBV0RERGRSa6s1k8oYlk+U9OWJfW8bic5PnfKpi43tXfSEghN2W22Ll5eTEsgxJYjjd3HaloD3ZX05TOyANhTqaArIiIiIpNYvPFM/AOuSKqlci/dI/XtAMydghVdgHOXFuF2Gp7Yc2L6cnVLkJLs6Nro0lwf2V4X/+/PO3jXLS9y50tHUjXUlFLQFREREZnk9lS14nYaFhROrQ6zMnkVZ3tSNnX5SEM06M6fov89ZHpcnLmwgMd7BN2alkD3lHGHw3DXh8/k5vMWUusP8qU/7aA10JWq4aaMgq6IiIjIJLe3qoVFRZlqRCUTRnGWl8rmANba7mNP7q3hz68dH/PXPlLXBkzdii5Euy8fqPFzpL6NSMRS6z9R0QVYXZrDZy9fzj9fvARIbQfsVNF3QxEREZFJbm9Vq6Yty4Ry5sJ8KpsD/GNnFQB1/iCf+v1Wvv3wnjF/7SMN7ZRke6bc1kI9XbS8GIAn9tTQ2N5JV9hSEqvo9lScHT0W32d3OlHQFREREZnEmju6qGgOdHdaFZkI3nHabJYUZ/LNh/fQGYrwvUf20RoIUdEcoKMzPKavfbS+nXn5U3Pacty8ggwWF2fyxJ6a7mptcY+Kbly8yjua9dLBUJj7tpRT0dQx4nukgoKuiIiIyCQW30JEFV2ZSFxOB//55hUcqW/ni3/azh9eOcrC2JrZw/VtY/rah+vbmDtFOy73dPHyYl46WM/B2uifZ0n2yRXdeNAdTUX37zuq+Ld7X+ecbz/B9b9+mZ0VzSO+13hS0BURERGZxPZUtgCwTEFXJpgLlhVz7pJC7tlcTn56Gv/99jUA3cFsLHR0hqlpDTJ/GgTdi5YX0xW23P9qORBdF91XpsdFRpqT6lFUdHdVtuB2Gv7pwsVsL2/is/dtG/G9xpOCroiIiMgktqeqlSyvi5k5J3/IFUm1/3zzCnJ8br5wxQpOmZ0DwKE6/5i93tFYx+W5BVN76jLA+nl5ZHtdPLU32n25qJ81uhCd0lw9ig7Ye6taWVSUyacvXca/XLKUnRUtbC+f+FVdBV0RERGRSSzeiMoYk+qhiJxk+YxsNn/xEt6xfjbpadEfyCS7ohvoCtPQ1gnAkdi06HlTuONynMvp4IJlxUQs5PjcAzbfKs7yUDuKiu6eylZWzIz2ALhqXSkel4M/vHJ0xPcbLwq6IiIiIpOUtZa91a2atiwTWs9trxYWZXCwLrlB9xt/281lP3yGjs4wR+qjFd1502DqMsDFK6Ldl/tbnxtXMoqKbnN7F1Utge7vMTnpbt68ZiZ/fq2C9s7QiO45XhR0RURERCapiuYArYGQOi7LpLGgMIODtf5e++uO1osH66ltDfKHV45ypKGNHJ+b3PS0pN1/Ijt/aREOQ689dPsqyfZQ3RIY0Z/5nqqTewBcu3Eu/mCIv26rHP6Ax5Er1QMQERERkZHZG/sQqo7LMlksKMykJRCioa2TgsyBq5CJau7o4kCNH2Pgl88cZG5B+rSp5gLkpqdxw9nzWViUOeA5JdleAl0RWgIhcnzuYd1/bz9d3U+fn8eiogzufPEIc/LS8aU5WVCQQU768O491hR0RURERCapbeXNGKOgK5PHwqJok6hDdW1JCbrbypsAuOkNC/jls4eoaA7wllNmjvq+k8mX37pq0OeLu/fSDQw76O6paiXH52ZGj4qxMYb3njGPr/51F+/55UuxY7CsJIs3LC7kfWfOY35h6puBKeiKiIiITFKvHm1iaXEWWd6JVUkRGUh8L92DtW1smJ8/6vu9drQJY+CTFy3hhbJ6dla0TKuKbiJKYt2Yq1uCLCkZ3g/F9lZFewD0bXZ3w9nz2TA/D38wRHswzK7KFl453MDtLx7m1ucPccmKEr5x9ep+tzwaLwq6IiIiIpNQJGLZerRx2lWvZHKbnZeO22mS1pBq67EmFhdlkuNz8/ELFvOJu15l/jTYWmg44ut3q1uG15DKWsveqlbeflrpSc85HYZTZud2//6SlSVAtGp850tH+NlTZfzq2UN84YoVIx/4KKkZlYiIiMgkVFbrpzUQ4tS5eakeikjCnA7DvIKMYe+l+8dXyymr7X2NtZbXjjWxbk4uAG9aPYOfvvc03nLKrGQNd0oojnVk7tt52VrL47urB+yeXN7YgT8YGlZX9+JsL5+5dBmnzs3l5UMNIx90EijoioiIiExCW482AXCagq5MMtHOy4lXdMsb2/n0Pa/z+T9u73X8aEM7DW2d3T/scTgMV6yZiS+t//1kp6v0NBdZXhc1ffbS/cu2Sm68fTP3bSnv97q9VfFGVMPv6r5xQT47jjfTFkzdFkQKuiIiIiKT0KtHG8nxubvXPIpMFguLMjhS3044kth2N3+LbWPz8qEGthw5USV87VgTQHdFVwZWku2lpkdFty0Y4r//thuAHceb+70m3nF5JPt0b1xQQChiu38glwoKuiIiIiKT0KtHGzl1bi4Ohxn6ZJEJZGFhBp3hCMcbOxI6/y/bKlg+I4vcdDc/e6qs+/jWo02kpzlZWjLw1joSVZzlobpHRfenTx2gqiVAaa6PXZUt/V6zp6qV2Xk+Mj3Db+u0fl4eDgMvH6of8ZhHS0FXREREZJJpCXSxv8avacsyKc2LNYs60jD09OWDtX52HG/hnetn84Gz5/PY7pruKbVbjzWxpjQHl1ORZigl2d7uZlSH69r45TOHuPrUUt6ydib7qvx0hSO9zg90hXl2f+2IewBkelysLs1hUwrX6epfhYiIiMgk89rRJqzV+lyZnPIz0gBo7uga8ty/xqYtv/mUmdxw1nzS05x86U87+NTvt7LjeLOasSWoONtDTUsQay3/88he3E7D5960nFWzcugMRzhQ07vR14OvV9DU3sV1G+eO+DU3zs9n67EmgqHwaIc/Igq6IiIiIhNYOGKxtvdaxlePNmIMrJ2Tk6JRiYxcji+67/NQQdday4OvV7Bxfj4zc3zkZaTx/jPn8fLhBjYdqufy1TN4z8Y54zHkSa8ky0tnOMIrhxt5aHslHzhnPiXZXlbOjDaa2llxYvqytZbbXzjM0pJMzlw48r2ONy7IpzMUYVt5/2uAx5r20RURERGZIB7YWs7eKj+fe9Py7mMf/90WqlqC/O6mM8j0uLDW8mJZPctKssjyulM4WpGRyfYmFnT3VrdyoMbP165c1X3s3y9bxo1vWEBRlgdjtD49UfG9dP/rwZ343E5ufMNCINoB2+d2squiBdZHz331aBM7K1r4+lWrR/VnfPr8aEh++VBD9+PxpIquiIiIyATQFY7wzYf2cMvTZWw+HF3XtuVII//YWc3rx5r4599vJRyxfONvu9l0qIG3rtVeoTI5ed0O0pwOWjoG3nomErF86+E9pLkcvGnNzO7jLqeD4myvQu4wlcT20t1V2cL7z5rXPX3c6TAsn5nFrsoTVdc7XjxMlsfF1aeWjuo18zLSWFaSlbJ1ugq6IiIiIhPAo7uqqWkNkuZ08N1H9mKt5cdP7Ccv3c0XrljO43tqePOPnuVXzx3iA2fP5+MXLEr1kEVGxBhDts89aEX3Ny8c5qm9tXzxzSsozPSM4+impnhF1+t28OFzF/Z6buXMbHZVtGCtpaYlwEPbK3nnhtlkjKDbcl9nLMznlUMNBLrGf52ugq6IiIjIBPC7TUcozfXxH29azksHG7jl6YM8tbeWm85dyM3nLeJD5yxgT1UrN5w1jy+/daUqWjKpZftctAwQdHccb+bbD+/hkhXFvP/MeeM8sqmpKMtDepqT958576QfHKyalUNLIER5Ywffe2QfAB84e35SXveSFSV0dIV5bn9dUu43HFqjKyIiIpJiB2v9PH+gnn+7dCnvO3Mutz57kG//fQ/ZXhfXnxX9oP/FN6/g7aeVsmpWtkKuTHo5Pjctgf6D7hce2E5uupvvvHOt/q0nidft5NFPn09J1snV8ZWzog2p7t18jHu2HOOmNyzo3gJqtM5cWECW18U/dlZxycqSpNwzUaroioiIiKTY7zYdxeUwvOv0OXhcTj518RIAPnjOgu6GUw6HYXVpjj74y5SQM8DU5Tp/kG3lzXzwnAXd60glOUpzff3uObysJAuHgR8/eYC89DQ+edGSpL1mmsvBRcuLeWx3NaE+e/WONQVdERERkRRq7wxx35ZyLls9g+Ks6Dq6azbM4YfvXsfHtA5Xpqhsb/9B9+VY46IzRrGtjQyPL83JoqJMrIXPXLq0e/unZLls1Qwa27t45XBjUu87FAVdERERkRT6zfOHae7o4kPnLOg+5nQYrjq1FK/bmcKRiYydHJ+73zW6mw7W43M7WVOqPaLH03lLi1g3J5d3b0j+vsTnLy0izeXgkV1VADz4egUPba9M+uv0pTW6IiIiIinS2NbJLU+VccmKEtbPy0v1cETGTXSNbghrba/p+JsONbB+Xh7ufqbYytj50ltWnvR3kSwZHhfnLi7kkZ3VWAu3vXCY2Xk+ruixbdRY0L8gERERkRT52dNl+DtDfPbyZakeisi4yva5CEcsbZ0ntp1pau9kb3UrZyzQtOVUGMv1/5etmsHxpo7ukFvZHBjzNbsKuiIiIiJjzFpLa58Os/EPfW8/dTZLS7JSNDKR1IivA+25TvflQw1YC2csLEjVsGSMXLZqBmcsyOc77ziFf7poMeGIpbI5MKavqanLIiIiImPsns3H+I/7t7O0JJOzFxVypL6NF8rqwcK/vjF5HU5FJovsWDfx5vYuSnN9QDToelwO1s7R+typJifdzd0fOQuAFw5E99Q91tDOnPz0MXtNBV0RERGRMfZiWT05PjfFWV7u2nSUGTlerjtjLm8/dTaz88bug57IRBWv6PbcS3fToQZOnZuLx6UmbFNZPNwea2wf09dR0BUREREZYzsqWjh9fj6/umED4YjFYcZ2PZzIRJfdZ+pyS6CLnRXNSd3DVSammTlenA7DsYaOMX0drdEVERERGUNtwRBltX5Wl2YD0a2DFHJluuu7Rnfr0SYiFjWimgZcTgczc7xjXtEdcdA1xiwzxrzW46vFGPMvxpj/MsYc73H8ih7XfN4Yc8AYs9cYc1mP4+uNMdtjz/3I6Lu/iIiITBG7K1uwFu0LKtJDvKIb30v3cF0bgBqzTRNz8tI51jBBg661dq+1dp21dh2wHmgHHog9/YP4c9bahwCMMSuBa4FVwOXAT40x8Qn4PwNuBpbEvi4f6bhEREREJpLtx5sBWK2gK9Ity+PCmBNBt6KpgzSXg8LMtBSPTMbDnHwfxxonx9Tli4Eya+2RQc65EviDtTZorT0EHAA2GmNmAtnW2hettRa4A7gqSeMSERERSantx5spyvJQku1N9VBEJgyHw5DlcXVPXS5v6qA016dp/dPEnLx0aluDBLrCQ588QskKutcCv+/x+08aY7YZY35tjMmLHSsFjvU4pzx2rDT2uO9xERERkUlv5/EWTVsW6UdOupuWQAiA440d3dsMydQX77xcPoZV3VEHXWNMGvA24N7YoZ8Bi4B1QCXwvfip/VxuBzne32vdbIzZbIzZXFtbO5phi4iIiIy5js4w+2taWT0rO9VDEZlwcnzu7opuRZOC7nQyJz/6dz2WDamSUdF9E/CqtbYawFpbba0NW2sjwC+BjbHzyoE5Pa6bDVTEjs/u5/hJrLW/sNZusNZuKCoqSsLQRUREZDqJRCzv+vmLXPfLl9hb1TrouX95vYLGts5Rvd7uqhYiVutzRfqT7Y0G3WAoTE1rkFkKutPGnNj+4eVj2JAqGUH3PfSYthxbcxt3NbAj9vhB4FpjjMcYs4Bo06mXrbWVQKsx5sxYt+XrgT8nYVwiIiIivTxfVsfLhxrYfLiRK370LN/++x6iLUJ6213Zwj/9fis/fGzfqF5vhxpRiQwox+empaOLyqYAAKV5CrrTRVGWB4/LMaYNqUYVdI0x6cAbgT/2OPyd2FZB24ALgX8FsNbuBO4BdgF/Bz5hrY2vPv4Y8CuiDarKgIdHMy4RERGR/tz+whEKMtJ49j8u5M1rZvKzp8rYV+0/6bxHdlYD8MDW46NqlrK9vJmCjDRm5qgRlUhf8anLx5uiYUdTl6cPYwyleb4x3WJoVEHXWtturS2w1jb3OPZ+a+0aa+0p1tq3xSq28ee+Ya1dZK1dZq19uMfxzdba1bHnPmn7+9GqiIiIyCgca2jn8T3VvGfjXEqyvXz28mUAPH+g7qRzH9lVRV6sUc5D2ytPej5ROypaWFWao06yIv3I9rlpCSjoTldz8tIn/BpdERERkQnvt5uO4DCG9545F4DZeenMK0jnhbLeQfdYQzs7K1r42AWLmF+Qzh9eOdbf7YYUjljKavysmJk16rGLTEU5PjeBrgiH6towBmZo5sO0Miffx7GGCTp1WURERGQyCHSFufuVY1y2qoSZOSeqRmcvKmTTwQZC4Uj3sUd3RactX7pyBu86fQ4vH2qgrPbk6c1DKW9spzMcYVFh5ujfgMgUlO1zA9E18SVZXtJciibTyZy8dJo7umgJdI3J/fWvSURERKa8nz55gKb2Lq4/a36v4+csLqA1GGLb8e5VWDyyq4plJVnML8zgnetn43IY7hlBVfdgbRsAC4syRjV2kakq2+sCokF3Vq6qudNNfC/dsVqnq6ArIiIiU9rju6v50RMHeMdpszljQX6v585aWADAC7F1uo1tnbx8qIFLV5UAUJzl5aLlxfzpteP9dmceTLwKvLBIFV2R/uTEKrrVLUFKY9vNyPSxfEZ0WcfLhxrG5P4KuiIiIjJlHalv41/vfo1Vs7L5xtWrT2oKVZDpYcXMbF4oqwfgoR2VRCxctmpG9znnLi2iuiU47LVkB+vayE13k5+RNvo3IjIFxacugxpRTUcLizJZMTObP79WMSb3V9AVERGRKesLD2zHGMMt71uP1+3s95xzFhWw+Ugjj++u5qt/2cXa2TmsmpXd/fyGeXkAbD4yvKrDwVo/Cws1bVlkIDm9gq6mLk9HV66bxWvHmjhan/zpywq6IiIiMiW1d4bYdLCB92yc270WrD/nLC6kMxThpjs2s6Awg998cGOvyu/SkiyyPC42H2kc1usfrG3TtGWRQfQKunmq6E5Hb107C4AHXz+e9Hsr6IqIiMiUtPlwI6GI5axFBYOed/qCfLxuB0uKM/ndTWecNNXY6TCcNi+PzYcTr+i2BrqoaQ2qEZXIILK9J4LuLE1dnpZKc32cPj+PP79WMew+CENR0BUREZEp6aWD9bgcpnvq8UAyPS7++k/ncv/HzqYg09PvORvm5bGv2k9ze2LbYByqi3Vc1tZCIgNKcznwxZYUaI3u9PW2daXsr/Gz5UgjP358P2//6fNJ6cSsoCsiIiJT0osH6zlldg4ZHteQ5y4uziSrR3Wpr/Xzo2H51aOJTV+Oby20SBVdkUHl+Nxke12D/vcnU9ub18zE5TBc8/MX+d6j+9hxvIV//sPWXvubj4SCroiIiEw5bcEQ28qbOXPh4NOWE7VuTi5Oh0m4IdXBWj8OA3MLtGWKyGCyfS5NW57m8jPSeN+Z8zh/aRF/+sQ5fPdda3n1aBM/euLAqO479I84RURERCaZVw43EE5gfW6i0tNcrJ6VzSuHE6voltW1MSc/HY+r/07PIhJ19qJCfGn672S6+6+3rep+vG5OLk/vreX/ntg/qnsq6IqIiMiU89LBBtxOw/oh1ucOx/p5+fxu0xE6QxHSXINPijtY26athUQS0DPgiMR95cpVbD7SwKFR3ENTl0VERGTKeelgPWtn55Kelryf6W+Yn0cwFGFnRfOg50UilkN1fm0tJCIyQpkeF3d9+MxR3UNBV0RERKYUfzDE9uPJW58bd/r8fABeKKsf9LyK5g4CXRFtLSQiMgqj7cStoCsiIiJTyrP7aglHLGcnaX1uXFGWh9Wl2Ty1t2bQ83ZXtgLaWkhEJJUUdEVERGRKeWDrcYqyPGxckJ/0e1+wtJhXjzbR3NH/frrP7Kvl0/e8RlGWh1Wl2Ul/fRERSYyCroiIiEwZjW2dPLm3hivXzsLlTP7HnAuWFRGOWJ7bX3fSc/dvKeeDt71Caa6PBz5+NtnaF1REJGUUdEVERGTK+Ov2SrrClqtPKx2T+6+bk0u218XT+06evvyTJw+walY2933sbGbnaf9cEZFUUtAVERGRKeOBV8tZVpLFypljM23Y5XRw7pIint5Xi7W2+3gkYilv6uCshQVkerR7o4hIqinoioiIyJRwuK6NV482cfVppRhjxux1zl9WRHVLsLvpFECdP0hnKEJp3ui6hIqISHIo6IqIiMiU8MDW4xgDV66bNaavc8HSIgCe6jF9ubypAxj9dhgiIpIcCroiIiIy6Vlr+dNrxzl7UQEzc8Y2bBZne1k5M5tn951oSHW8MRZ0VdEVEZkQFHRFRERk0nv1aBNH6tu5at3YNKHqa+2cHPZVn5i6fFwVXRGRCUVBV0RERCa9B7aW43U7eNOamePyeouKMqlv66SxrROIVnRzfG6ytKWQiMiEoKArIiIik1pnKMJft1Vy6coZ49bxeFFRJgBltX4AyhvbVc0VEZlAFHRFRERkUntybw1N7V1jtndufxYX9w66x5s6tD5XRGQC0UZvIiIiMun85MkD3LXpKB96wwJeOFBHYaaHcxcXjtvrz8r14XE5KKttw1rL8cYOzl40fq8vIiKDU9AVERGRSedPW49T3xbka3/dBcCHzlmAyzl+E9WcDsOCwgzKavw0d3TR1hlmtiq6IiIThoKuiIiITCpVzQH21/j5/JuWc9q8PB7Yepwbz10w7uNYVJzJzuPNlDeq47KIyESjoCsiIiJjqi0Y4sHXK3h6by0b5udx5bpSirI8I77f8wei+9e+YUkhq2blcPr8/GQNdVgWFWXy8PZKDtW1ATA7Lz0l4xARkZMp6IqIiMiYuXfzMb7yl134gyEKMz38fWcV33x4D9dtnMtX3rYKh8MM+57PHaijICONFTOyx2DEiVtUlEHEngjeakYlIjJxKOiKiIjImAiGwnzr4T0sKsrg/711JafNzaOs1s+vnz/MnS8dAeCrV67CmMTDrrWW5w7UcfbiwhGF5GSKd15+el8tPreTvHTtoSsiMlFoeyEREREZE//YWU19WyefvnQZ6+flY4xhcXEW37hqNTeft5A7XzrCt/++d8Drb3m6jE0H63sd21ftp7Y1OK4dlgeysDAadCubA5Tm+YYV2EVEZGwp6IqIiMiYuGvTEebk+04KpcYYPv+m5Vx3xlxuebqM1481nXTtliMNfOvhPXzotlfYXdnSffy52DThc5akPuj60pzdDajUiEpEZGJR0BUREZGkK6v189LBBq49fW6/U4yNMfzbpcswJjr1t69fPnOIHJ+bTK+Lm27fTG1rEIDn9teysDBjwgTLRbHpy1qfKyIysSjoioiISNL9ftNRXA7DNRtmD3hOfkYaa0pzeHZ/76B7uK6Nf+yq4v1nzuPWG06noa2Tt/3fc1zxv8/y3IE63jABqrlxi4oyAFV0RUQmGgVdERERGdTju6u55PtPs+VIQ/ex9s4QZbX+fs8PdIW579VyLl1VQnGWd9B7n7ukkFePNtEa6Oo+dutzh3A7HFx/9jxWl+Zwy/vXs6Qki1m5Xq5YM5Prz5qXnDeWBIuKohXd2aroiohMKOq6LCIiIgPq6AzzpT/toKI5wHt/tYmfvvc0IhH4f3/eQVVLgB+/5zTefMrMXtfc+twhmtq7+MDZC4a8/7lLivjJk2W8WFbPpatm0NDWyb1bjnH1qaXdIfn8pUWcv7RoTN7faK2fl0ea08GqWTmpHoqIiPSgiq6IiIgM6BfPHKSiOcBP33saS4qzuPH2zdx0x2YyvS5OmZ3Lv9y9lSf31HSfX9sa5KdPHuCNK0vYuCB/yPufNjeP9DQnz8SmL//kyQMEQxFuOnfokDwRrJiZza6vXta91ZCIiEwMquiKiIhIvyqaOvjZ0wd485qZXLFmJuctLeK/HtzJwqIMbnrDQgKhMNf98iU++tstfPsdp3Dluln88LF9BEMRPv+m5Qm9RprLwVkLC3h2fx07jjfzm+cPcd3GuSwpyRrjd5c8LqfqBiIiE42CroiIiPTrO3/fg7XwuVhozfS4+O41a7ufT3M5uP2DG/nQba/wL3e/xq+fP8SO481cf9Z8FhYlXuE8d0khj++p4Z9+v5X8jDQ+e1liIVlERGQg+hGkiIiInKS8sZ0HX6/gA2fPZ05++oDnFWR6+OPHz+E77zyFyuYAWV43n7p4ybBe69zY+ttDdW186S0ryUl3j2rsIiIiquiKiIjISX770lEArj97/pDnOh2Gd22Yw1tPmUVbZ4j8jLRhvdbCwgwWFkX3xn3b2lkjGa6IiEgvCroiIiLSS6ArzB9eOcobV5YMa39YX5oTX5pz2K9njOGBj52Dx+3AGDPs60VERPpS0BUREZFeHnytgqb2Lm5IoJqbLJquLCIiyaQ1uiIiItLNWsttLxxmWUkWZy0sSPVwRERERkRBV0RERLq9Xt7MrsoWrj97nqYRi4jIpKWgKyIiIt1ePlQPwGWrZqR4JCIiIiOnoCsiIiLdth9voTTXR2GmJ9VDERERGTEFXREREem2vbyJ1aXZqR6GiIjIqCjoioiICAAtgS4O17ezpjQn1UMREREZlVEFXWPMYWPMdmPMa8aYzbFj+caYR40x+2O/5vU4//PGmAPGmL3GmMt6HF8fu88BY8yPjLpfiIiIjLsdx5sBWDM7N7UDERERGaVkVHQvtNaus9ZuiP3+c8Dj1tolwOOx32OMWQlcC6wCLgd+aoyJ7yr/M+BmYEns6/IkjEtERESGoTvoqqIrIiKT3FhMXb4SuD32+Hbgqh7H/2CtDVprDwEHgI3GmJlAtrX2RWutBe7ocY2IiIiMk23lzZTm+sjPSEv1UEREREZltEHXAo8YY7YYY26OHSux1lYCxH4tjh0vBY71uLY8dqw09rjvcRERERlHO443q5orIiJTgmuU159jra0wxhQDjxpj9gxybn/rbu0gx0++QTRM3wwwd+7c4Y5VREREBtDcEW1Edc2GOakeioiIyKiNqqJrra2I/VoDPABsBKpj05GJ/VoTO70c6Pl/z9lARez47H6O9/d6v7DWbrDWbigqKhrN0EVEZAIIRywf+M3L/OTJA6keyrS3U+tzRURkChlx0DXGZBhjsuKPgUuBHcCDwA2x024A/hx7/CBwrTHGY4xZQLTp1Mux6c2txpgzY92Wr+9xjYiITGF3vHiYp/bW8tuXjhBt0yCpsl1BV0REppDRTF0uAR6I7QTkAu6y1v7dGPMKcI8x5kbgKHANgLV2pzHmHmAXEAI+Ya0Nx+71MeA2wAc8HPsSEZEprKo5wPce2UeOz01lc4CdFS2sVsgad9Zath5r4m/bKynN9ZGnRlQiIjIFjDjoWmsPAmv7OV4PXDzANd8AvtHP8c3A6pGORUREJp+v/nUnXeEId954Ju/42Qs8uqtaQXec/H1HFXe+dJj2zjA1LUGON3XgcTn43JuWp3poIiIiSTHaZlQiIiLD9vjuah7aXsW/XbqUU+fmsX5eHo/uquZf37g01UOb8mpaA3zmntfITU9jYVEGM+d4+eeLl/CmNTPI8rpTPTwREZGkUNAVEZFx1dzRxRce2M6ykixuPm8RAG9cWcJ/P7SH400dlOb6UjzCqe1//r6XznCE3950BgsKM1I9HBERkTEx2n10RUREhuXrf91Fnb+T716zljRX9H9Dl6woAaKV3kBXmN88f4j91a39Xl/R1MFPnjzA5/+4jQ/fsZlDdW3jNvbJblt5E/duKedD5yxQyBURkSlNFV0RERlTbcEQP3p8PxkeFw4D924p5xMXLmLN7BPrcRcWZbKwKIPfv3yMO148woEaP5esKOZXN5ze616BrjA3/Ppl9tf4KcxMo6Gtk0VFmVpbmgBrLV/5yy4KM9P45EWLUz0cERGRMaWKroiIjKk7XzrCz585yPcf3cd3H9nH0pJMPnXxkpPOe+PKEnZXttAWDHHukkKe2VdHS6Cr1zk/enw/+2v83PbB09n8xTdy5sICnthTPV5vZVJ7Zn8dW4408plLl2ktroiITHmq6IqIyJgJdIW59blDnLukkF9ev4HjTR0UZnrwuJwnnfvhcxdSmOHh3RvncKDGz9t/+gKP7arm7afNBuD1Y03c8nQZ79owmwuWFQNw0fJivv633RxraGdOfvq4vrfJ5lfPHqQk28M7Yn+eIiIiU5kquiIiMmb++OpxaluDfOyCRXjdThYVZZLj67+aWJjp4cPnLSTb6+bUObnMyvHyt22VQDQw//t9r1OU5eE/37yy+5qLlkcD75N7a8b+zUxiuytbeHZ/HTecPb97XbSIiMhUpv/biYjImAhHLD9/poy1c3I5a2HBsK41xnDFmpk8u7+O5o4uvvfIXvZV+/nW20/pFZQXFmWyoDCDx3cr6A7mV88ewud2ct3GuakeioiIyLhQ0BURkaSz1nLv5mMcqW/nY+cvwhgz7HtcccpMOsMRvvG3Xfzy2UO878y5XBir4PZ04bJiXjxYT3tnKBlDn9AiEcv+6lZa+6xdHkx1S4AHXz/OuzbMJjc9bQxHJyIiMnFoja6IyBQXDIX5waP7mZPv440rSyjO8o7qftZatpU3s+VII9vKmwhFLOlpTtLTXPjSnFgLj+yq4mBtG8tnZHHpypIRvU58+vI9m8tZWJTBf16xst/zLl5RzK+fP8TTe2spq/Xzu01HOWdxIR8+dyHLZmSN5q2mnLWWAzV+XjxYz4tl9bx0sJ7G9i5m5ni588aNLC4++f1VNQdoaOukvi3IC2X1/H1HFaGI5UNvWJCCdyAiIpIaxlqb6jGMyIYNG+zmzZtTPQwRkQnvmw/t5ufPHATAGHjnabP5n2vWjvh+3/n7Hn76VBkAM7K9+NKctHeGaO8M09EZJhSxbFyQzztOK+WKNTNH1eH3mw/t5tbnDvHHj5/NKbNz+z2nMxThtK89SjAUpitsOX1+HjuOt9DRFebKdbP476vXkOGZfD/XjUQsN9+5mcdi07JLc32cubCAtXNy+NHjBwhHIvzmgxtZNycXiIbi/3pwJ7e/eKT7Hi6HYeOCfK47Yy5vOWVWKt6GiIjIiBljtlhrN4zk2sn3f34RERlQVzjC//vzTtaU5nDt6XN46VA9v3j2INedMZfrz5rHb547zN2bj3H1aaWcvahw2PffU9XCz585yNvWzuLzVyxnZo7vpHPCEYvTMfypyv351zcu5dqNc1lQmDHgOWkuB285ZSbP7Kvlq1eu5pKVJTS2dXLrc4f46VMH2FvVyi/ev4G5BZOrK/Otzx3isd01fPLCxbxrwxzm5Pu6p4Cfv7SI9926iff84iW++JYVXLdxLv/3xAFuf/EI79k4h/OXFpHtc7NqVs6Azb9ERESmMlV0RUSmkJ88eYD/+cdeAM5YkM/RhnZ8bid//dQbSE9zEegKc8H/PMXsPB/3fvQsjDFUNncQsdGK4WAiEcu7fv4iB+vaePzT55OXMXHWe0YiFmM4aS3w0/tq+ae7XsXa6D69Fywv5tKVJXjdJ29vNJHsON7M1T99nouWF3PL+9b3u8a5piXAv97zGs8fqGfVrGx2VrRw9amlfO+atTiS9IMGERGRVFJFV0REKKv187+P7+dNq2dwwbIivv633XR0hnng4+eQnhb9du91O/nERYv50p928Mz+OjLSnHzotlcIhCJ86qLF3HzeogG3n7lvSzmbjzTynXeeMqFCLjBgsDt/aREPfvIN/OCxfTyxt4Y/bj3O208t5fvvXje+AxxAoCvMR3+7hdrWIMaA1+UkPyONnRUtFGR4+NbbTxmwkVdxtpff3ngGv9t0lP9+aDfnLink2+84RSFXREQEVXRFRKaESMTy7l+8yL5qP49++jyKs7zUtAaobQ2yalZOr3M7QxEu/O5TuJyGquYApbk+ls/M4qHtVSyfkcWvP3A6s/pUd18+1MCNt73C8plZ3H3zWZMyTIUjli/9eQf3bj7GS5+/mIJMT6qHxMPbK/nY717lrIUF+NKcdHSGaWjrpCsS4ZtXr+GMBLdl8gdD+NzOpE0ZFxERmQhU0RURmeb+uPU4rxyOVlvjXZWLs7z9dlhOczn41MWL+Y/7t3PK7Bx+84HTKcj08Niuav717tf4wG9e5t6Pnt29tvPRXdV88q5XKc3z8b/XnjopQy6A02H4wNnzuWvTUR7Yepybzl04rOsb2zqTXsl+8PUKCjM9/PamM0YVUjMnYbMtERGRsaR9dEVEpoC7Nh1hSXEm16yfndD571w/h5+/fz2///CZ3ZXNS1aW8PP3r+dQXRs337GZFw7U8Zl7Xucjd25m+Yws7vvo2SdVeiebpSVZnDY3l9+/fJThzGgqq/Wz4RuP8ZvnDyVtLK2BLh7fU8NbTpmpSqyIiEiSKeiKiExyB2v9vHq0iXesnz3ges6+nA7DZatmnLTtztmLC/nuNWvZdKiB6361iX/srOI9G+dy14fPJH+CrcsdqWtPn0tZbRubjzQmfM2ju6oJRyzfengPZbX+pIzjkZ3VdIYivHWttv0RERFJNs11EhGZ5P746nEcBq4+tTQp97tyXSkel4OOrjCXrZrR3chqqnjL2pl89a+7+P3LRzl9fn5C1zyxp4b5Bek0dXTxb/e+zr0fOYvG9i52VDRzwdKihH/A0NODr1cwO8/HaXNzh32tiIiIDG5qfXoREZlmIhHLA1uPc+6SIkqyT16PO1KXr56ZtHtNNOlpLt62bhb3bynnG1etwZc2+FZDze1dbDnSyEfPX8jSkiz++Q+v8ab/fZayWj8RCz9//3ouWzUjodd+YGs5XpeTNbNzeO5AHTeft3BEIVlEREQGp6nLIiKT2EsH6zne1ME7ElybK1HnLi4kGIpwoGboacjP7K8lHLFctLyYt62dxbs2zMYCn7xwMbnpbv6+oyqh19xd2cK/3v06H/vdq5z7nScJRyxv07RlERGRMaGKrojIJHbflnKyvC4uXVmS6qFMKouLM4Fok6k1s3MGPffJvTXkprtZNycPYwzfeefa7ucqmgP8Y2cVnaHIgPsPx93x4hE8Lgc/ue40njtQB8DyGVmjfCciIiLSHwVdEZFJqqGtk4d2VHL1qbPxugeffiu9zSvIwOkwQ1Z0IxHL03trOX9pUb+dkS9fNYP7tpTz0sF6zltaNOB9mtu7+NPW41y5bhaXrCzhEv1gQkREZEwp6IqITFJ3vHiYQFeED50zP9VDmXTSXA7m5af36qBc1Rzg0V1VFGR6mJHjZWFhBofq2qhv6+Si5cX93ucNSwpJT3Py951VJwXdR3ZWUZLtZe2cXO7dcoyOrjA3nD1/LN+WiIiIxCjoiohMQh2dYW5/4TCXrChmSYmmv47EwqLMXkH3J08e4M6XjvQ6x+d24jBw/gDVWq/byYXLinlkZzVfu3J1d9X3mX213HznFpwOw6cuWsL9r5Zz+vw8Vs0afJq0iIiIJIeCrojIJHTvlmM0tnfxkfMXpXook9bi4kye3ldDKBzB5XSw5UgjGxfk819vXUVlcwcHavzsrW5lbn46uekD7yF86aoS/ra9kq1HG9kwP5/a1iCfvud1lhRnsnJWNj94bB8A/37ZsvF6ayIiItOegq6IyCQTCkf45bMHOW1uLhvm5aV6OJPWoqIMusKWY40dFGd52FPVwicvXMzKWdmsnJXNxSsSW0d70fJi0pwOvvfIPt59+hzuf7Wc1kAXv7vpDJbNyOKCZUW8WFbP5asT24JIRERERk9BV0RkknloRxXHGjr44ptXag/WUYh3Xj5Q46eyqYOIhVNH8IODLK+bj56/kF8+e4gXD9YD8PWrVrMs1lH56lNnc/Wp2v5JRERkPCnoiohMIpGI5f+e2M+S4kzemGDFUfq3qMcWQ6FwBIDT5oysQv7pS5fxqYuXsL/GT21rkHOXFCZtnCIiIjJ8CroiIpPII7uq2Fft53+vXYejn+1uJHHZXjfFWR4O1PhpaOtkUVEGOenuEd/P5XSwYmY2K2YmcZAiIiIyIoPvbi8iIhOGtZYfP3GA+QXpvHmN0lQyLC7O5ECNn61HG1mv9c4iIiJThoKuiMgEc6iujc/dv42v/3UX4YjtPv7k3hp2VrTw8QsX43Lq23cyLCrKZFt5E43tXZw2V0FXRERkqtDUZRGRCSLQFeaLf9rBH18tx+kwdIUt9W2dfPeatWwrb+K/HtzF7DwfV59amuqhThmLizOJ/yzhNFV0RUREpgwFXRGRCeL7j+7jvi3l3PiGBXzk/IXc/fIxvvfoPvbXtLKrooWSbC8/es+puFXNTZpFRdGGVFleF4tjj0VERGTyU9AVEZkAth5t5FfPHuQ9G+fypbesBOCfLl6Cy+ngO//Yw7Wnz+ULVywnyzvyZklysvgWQ+vm5Kq5l4iIyBSioCsikmLBUJjP3reNkmwvn79iea/nPnbBIq4/ax4ZHn27Hgsl2R6WlWRx6aoZqR6KiIiIJJE+OYmIpEh7Z4gn9tTwh5ePsb/Gz28+cDrZ/VRsFXLHjjGGf/zreakehoiIiCSZPj2JiKRAS6CLS7//DFUtAYqyPHzuTcu5cHlxqoclIiIiMiUo6IqIpMDTe2upagnwg3ev5W1rS3FqfaiIiIhI0qh1p4hICjy5p4a8dLdCroiIiMgYUNAVERln4Yjlyb01XLCsWCFXREREZAwo6IqIjLPXjjXR2N7FRVqTKyIiIjImFHRFRMbZE3uqcToM5y0tSvVQRERERKYkBV2RMdQWDPGvd7/G8wfqUj0UmUAe313Dhnl55PhO3kpIREREREZPQVdkjITCET5516s8sPU4P35if6qHMy1FIpb91a2pHkYvFU0d7Klq1bRlERERkTGkoCsyDPuqW7n8h89woGbw8GSt5f89uJMn99aypjSHTYcaqGkNjNMoJe7R3dW88QfP8MI4VNQb2zq5Z/MxQuHIoOc9sPU4ABevUNAVERERGSsKuiLD8LW/7mJPVSv/98SBk547WOvn/57Yz023v8K533mSuzYd5WMXLOK716zFWvjHjqoUjHh621nRAsBPnyrrdbxriDA6XIGuMDfdsZnP3reNXzx7sN9zQuEI3/jbLv7nH3t5w+JCFhVlJnUMIiIiInKCgq5Igp7eV8uz++uYk+/jL9sqOdbQDsCeqhbe8uNnueh7T/PdR/ZxuL6ddXNy+eqVq/j3S5extCSTxcWZ/G17ZYrfwfRTVuMH4LkDdWwrbwLgfx/bzyn/9Qh/ilVWh2PH8Wae3leLtbb7mLWWz/9xO1uONLJ8RhY/fGw/ZbX+Xtf5gyGu//XL/PLZQ1x/1jx+/YHTMUbbComIiIiMFVeqByAyGYQjlm8+tJu5+enceeNGLv7e09z63CH+5ZIlfPiOzQS6InzpLSt585qZzMjxnnT9FWtm8uMn9lPTGsDndnLL02Vce/pc5uSnj2g8oXCELzywnfmFGXzs/EXdoam5vYs0lwNfmnNU73eqOFDj54wF+eyubOFnT5Vx5bpZ/OCxfeSlu/mXu19jZ0Uz6+fl82JZHRELX3nbKhwD7Gt7rKGd6375Ei2BEOcsLuDfL1tOY3snD2+v5IGtx/nMG5fy7o1zeOP3n+Fz92/j7pvPwuEwtAa6+MBvXuG1Y038zztP4ZoNc8b5T0FERERk+lHQFUnA/VvK2VPVyk+uO415BRlcua6UP7xylL1VrVQ1B7j7I2dx2ty8Aa9/85qZ/Ojx/dz54hEe213D7soWGtq6+Obb14xoPD96fD/3bC4HotNz//OKFfzy2YPc+eIRwtYyO8/HuUuK+MrbVuF2Ts+JG6FwhEN1bXzwnPmcPj+fnzx1gKf21rJuTi6/u+kMvvP3Pfzy2UP88tlDpDkddIYjnL4gn7etnXXSvYKhMJ+861Us8G+XLuUXzxzkqp88D4DTYXjvGXP55EWLMcbwpbes5N/ufZ0P37GZ0+bl8djuaraXN/N/7zmVN62ZOc5/CiIiIiLTk4KuyBDaO0N879G9nDo3lyvWzADgo+cv5P5Xy3nxYD3/ffWaQUMu0D19+cdPHCA9zcnq0mz+vqOSr125CtcAQbShrZNbnzvITW9YSF5GWvfxFw7U8eMnD/DO9bNZWpLJNx/ew9+2VeIwcM36OczK9bGrspm7Nh3FAF+/avW0nCZ7rLGDznCERcWZXLS8mF8+e5Asr4ufv389GR4XX7lyNW9aMxOnw7CmNIerfvI833tkL29aPeOkHw5886E9vF7ezC3vW8/lq2dw3RnzeGh7JQsKM1g3J5cMz4lvpe84rZSdFc08srOax/fU4HYa/u+6U7l8tUKuiIiIyHgZcdA1xswB7gBmABHgF9ba/zXG/BfwYaA2duoXrLUPxa75PHAjEAY+Za39R+z4euA2wAc8BPyz7bkITiSFfvXsIapbgvzkutO6A+OSkiw+cv5CPE4H150xd8h7GGN4/5nz+MUzB7nlfeupaO7gI3du4cWD9Zy7pKjfa370+H5ue+EwFU0BfvDudQDUtgb5l7tfY0FhBl+9chXpaS6WlGTxt22V3HzeQpaWZHVf/82Hd/Pzpw+ytCSLG86eP+o/h4FYazlS386uyhb2VbficzspzPSwfl4e8wszxux1h3Igtj53cXEmhZke7vrwmRRleijJPjG1/MyFBd2PP3v5Mj5022bufuUY7ztzXvfxJ/ZUc9sLh/nQOQu4fHX0Bx35GWm9zunJGMOX37qKL791Ff5giFA4Qm56Wr/nioiIiMjYGE1FNwR8xlr7qjEmC9hijHk09twPrLXf7XmyMWYlcC2wCpgFPGaMWWqtDQM/A24GXiIadC8HHh7F2ESSoqY1wP9v787jo6rOP45/nuwkIWEL+xJ2BESWACqo0KrVqj/cWrW27q1al1Zbu/26+NOudtHiUq2tS+uK1arFXeu+QRBkB0Eii2GHJISQbZ7fH3MDAUJCQpKZzHzfrxevzNx758xzDzN3znPPuefe/eZKTh7ZnbzcTnut+/HJhzWqrAuPzuWCo/phZgzulklGSiIzPy6sM9FdX7SLR2atpktmCv+eu47Tx/RibN8OXPzALIrKKnng4gmkp4S/vlOHdmXq0P1vVfODLw1j5cZSbpq5mPZpSZw5tvcBY5tdsJUZs9cwaVAXThrZnbTkhq/xLSwq48k5a/nXnLUUbNm53/qMlET+deXRHNYjCwgP/62oCtE+LbnBsptD7UQXYFy/+nvdpw7tyvjcjvz5tU84a2xv2qUkUlRWyY+fWsDQbu354clDGx1DZqoGzYiIiIhEQpNbYe5eCBQGj0vMbAnQq56XTAMec/dyYJWZrQAmmFkBkOXu7wOY2T+A01GiKxFSVFbJ8g0ldM5I4Z43P6WiKsQPThrWLGXX9AinJSdywvBuvLhoPb88Y+R+Q2XvemMFoZDz2LeO4vJ/5vOTpxbQu2M7lhaW8NcLxjG8Z1aD75WYYPz53NFc8sBsrp/xMbMLtvKL00bslcSWVVTz+5eWcf97q0hOSOCJOWvp+J9kLp3cn8uPG1jn9b2l5VXc8foK/v72KiqqQ0zs34nLjhnAEb07MLhbJlUh57MtpVzywGwufWA2T181icWFxdzwr/ls2VHOyF7ZTBnalaumDiQ1qeUmzVqxcQdd26eSdZCJtZnxw5OGcfbd73PxA7P43VmjuP2/K9i8o4J7L8hr0VhFREREpHk1S3eDmeUCY4APgUnA1WZ2AZBPuNd3G+Ek+INaL1sbLKsMHu+7XKTVzV29jW8//BGFRbt2L7vo6Fz6t8AQ3FNG9eTpeZ/z7orNTKnVI/v59jIem7WGr+T1ZlDXTH571ii+cvf7rNtexm3njOYLw7od9HtkpCbx8GUTufXV5dz5+krmrt7OneePZWBOJp9u2sG3/jmHFRt3cOFR/bjhpGF8vGY797+7ij+8vJznFqzn92ePYmSv7N3lvbiwkBufXcz64l2cNbY3135xEP067183I3pm8/cLx/PVe97n1NvfYWNJOUO6ZXLu+D588OkWpr/2CSmJxtVfGHxolViPFZt27O7NPVh5uZ245axR3DxzMSfe+hblVSGumjqQUb07tEyQIiIiItIiDjnRNbNM4Engu+5ebGZ/AW4GPPj7R+ASoK7ZcLye5XW917cID3Gmb9+Gr4sUOVhV1SEembWam2cupnt2GnedP5byqmqKy6o4c2zLnHc5dkgX2qcmcf+7BZRXhUhKMBZ/XszLizfgOFdNHQTA+NxO/PqMw8lMS6pzRuCGJCUmcMOXhjE+txPXz/iY/7n9HS6Z3J8H3isgOTGBhy6dyOTBXQCYNKgLkwZ14aVF6/np0ws57Y53+OKwbpw7vg//nreO5+YXMrxHFneeP7bBocAje2Uz/dwxXPPoXC6d3J8bvjR0d2/ylQ/N4Y7XV3D6mF707ti0WyzVx91ZuXFHk/7vvjq+D8cM6cIvnlnE9p2VXPvFlkvGRURERKRl2KHM+WRmycBM4CV3/1Md63OBme4+MpiICnf/TbDuJeBGoAB43d2HBcvPA6a4++X1vXdeXp7n5+c3OXYRCF83OmP2Gu59exWrt+7kuCE5/Pnc0a02edCPn5rPo7PW7LVscNdMLpqUy/kT657s6FAUFpVx7aNzmV2wjRE9s7jnG+MOmGgW7azkb+98yiMfrmZLaQXJicZ3vjj4gEOaD6Q65CTuc2/addvLOP6Pb3LckBzu/sa4Q9qnuqwv2sWRv3mNm6aN4IKjcpu9fBERERFpeWY2x93zmvTapia6Fr7Y8EFgq7t/t9byHsH1u5jZdcBEdz/XzEYAjwATCE9G9Row2N2rzWw2cA3hoc/PA7fXzNR8IEp049P6ol3cPHMxBVtK2VZawZi+Hbnja2OadPucyuoQlz6Yz1vLw/dWveK4gZw4vBsJCa13K56q6hCrt+5kZ0V1+FY4OZlkt2vZyZqqqkO8sWwTkwZ1oV1Kw9ed7qqs5s3lmxiYk9noocD1ufP1Ffz+pWV8e8pAMlKT2L6zglWbS1m1uZQ+ndI5/rBunDiiG13bpzVc2D7e+WQzX//7hzxy2USOHtSl2WIWERERkdZzKInuoQxdngR8A1hgZvOCZT8BzjOz0YSHHxcAlwO4+yIzmwEsJjxj81XBjMsAV7Ln9kIvoImopA4rNpZwwd/Dsw4fOaAznTNTeW5BIacs7MGXD2/cPUrdnR8+OZ+3lm/iV2eM5GsT+kbkXrNJiQkMyGm+5PFg3/P44Qd/nW9aciJfGtG92eO47Jj+PL+gkLveWAlASmIC/btkMDAnk2UbSvjp0wv53QtLefG6Y+nVoV2D5bk7H68tYkTPLFZsLAFo1sRcRERERNqOQxq6HEnq0Y0v89du54L7ZpGUkMADF49nZK9sqkPOKdPfpmRXFa9977gD3hJnW2kFAB0zwsORd1ZUhWcafreA608YomswI6iqOkRpRTVpyQmkJCbsPtng7ixYV8Q593zA5MFduPeChk/k/e3tT/nlc0vo3yWDThkpLN9QwvxfnBiRExgiIiIicugi1aMr0ipCIeeHTy4gPTmRx751FH07h68pTUwwfn7acL5274fc+9anXFNHwvrc/EK+/8THVFaHmDI0h4E5mczIX8O2nZV848h+XPOFQa29O1JLUmIC2e32v97XzBjVuwPfOX4wv31hKS8vWs+J9fQqLyks5pYXlzEhtxPbyyqY89k2xvbtoCRXREREJE4p0ZWo98LC9SwpLOa2c0bvTnJrHD2wCyeP7M5db6zk7Lze9MgOD3ENhZzbXl3O9P+uYGzfDozP7cTT89bx6pKNHH9YN644bgB5uZ0isTvSCJdO7s+/P1rHjc8uYtKgLmSk7n/I2lVZzXcfm0dWu2T+8vWxdEhPYeb8z+nTqflncxYRERGRtkGJrkS16pDzp1eWMbhrJqcd4NY6P/nyYby6ZAN3/HcFvzrjcAD++cFnTP/vCr6a15ubTx9JalIiPzhpGMVllbuHMEv0S05M4NdnjuSsv7zPzTMX89uzRu23zW2vfsKyDSU8cPF4OmemAjBttG7FLSIiIhLPDv4eISIR8My8dazcVMr1JwzZ7xY1Nfp0Suec8X2Ykb+GNVt3UrSzkltfXc6kQZ353VmjSE0KX7ubmGBKctugcf06cdXUgTw2ew2Pz16917rS8ioe+uAz/ueInkwZ2jVCEYqIiIhItFGiK1EpFHJeXbyBP7y0jBE9sxqc9ffqqYMxM27/7yf8+bVPKC6r5KenDNc1mjHi+hOGMnlQF372zCIWrC3avfzpeevYUV7FhUfnRi44EREREYk6GrosUWHLjnJ+9NQCCovKyEpLZt32Mj7bspPuWWncNG1Eg/e27Z6dxtcn9uPB9wsw4JzxfTisR1brBC8tLjHBmH7eGE67/R2ueGgOM6+ZTIf0ZP75/mcM75HF2L4dIh2iiIiIiEQR9ehKxK3ZupOz736ft5ZvIiczlcrqEH06pnP7eWN4+4dTGdfv4CaNunLKQFISE0hLTuT6E4a2cNTS2jplpHDX+WPZVFLOdx6fx6xVW1m6voRvHNVPPfciIiIishf16EpEffDpFq55dC4VVSEevmziIc2EnNM+lbvOH0tKUgI57VObMUqJFkf06cD/TRvBj59awMJ1RbRPTWLa6LonKRMRERGR+KVEVyJiy45yfv38Up78aC19O6XzyGUTGdyt/SGXO3WYJiSKdeeO78Pc1duYkb+Wi47OJT1FhzERERER2ZtaiNLqFn9ezEX3z2LbzgqumjqQq6cOpl1KYqTDkjbCzLhp2kgG5GTylXG9Ix2OiIiIiEQhJbrSaJ9tKaVHdjtSkhp/ifd7Kzdz+T/mkJmWxLNXT9aEUdIkacmJXHHcwEiHISIiIiJRSomuHLR128v43QtLefbjzzlyQCfuu2j87mGjuyqrKd5VSVlFNR0zUshKS97rtaGQ8+D7Bfzm+aX07ZzOPy6ZQM8O7SKxGyIiIiIiEuOU6EqDlm8o4aEPPmNG/hrc4cwxvXh63jouvn82vztrFA+8V8Ajs1ZTURUCID0lkUsm9eebxw4gJTGBZRtK+O0LS/jg061MHZrDreeMpkN6SoT3SkREREREYpW5e6RjaJK8vDzPz8+PdBgxbWPJLm54Yj5vLt9ESmICpx3Rk+tOGEzvjuk8M28d1z0+j5CH73F65phejOqdTbuUJN5cvon/fPw5KUkJu5PfzNQkfn7qcL6S11u3ghERERERkQaZ2Rx3z2vKa9WjK3X6aPU2rnxoDkVllfzgpKGcO74vnTL29MJOG92LtORE3l2xmUsn96df54zd684e15srjhvAE/lr6ZSRwqCumeTldqRr+7RI7IqIiIiIiMQZ9ejKfl5YUMi1j82le3Ya93w9j+E9NWGUiIiIiIi0LvXoSrN5ZfEGrnl0Lkf06cDfL8zTtbQiIiIiItLmKNGNQ9UhZ9HnRby/cgvvrdzC0vXFDOuexbDu7bn/3QJG9MrmgYvH036fmZNFRERERETaAiW6Ma68qppHPlxNfsE2Qu7srKjmo9XbKNlVBcDgrplM7N+ZJYXFvLl8EyN7ZfGPiycoyRURERERkTZLiW6M2lVZzYsL1/PHV5axZmsZfTulk5acQFJCAqeO6sGRAzpz1MDOe00QVVRWSfvUJBISNCuyiIiIiIi0XUp0Y8ziz4u5791VvLRwPSXlVQzr3p4HL5nAsYO7NHhbn+x26sUVEREREZG2T4lujCirqOa2V5fzt3dWkZ6cyJdGdufUUT04ZnAOieqhFRERERGROKJEtw1Yt72MZ+atI79gG92y0ujXOZ3UpAR2VYbYvrOCpetLWLCuiK2lFZw7vg8/OnmYZksWEREREZG4pUQ3ClVWh1i2voQ3l2/itSUb+Gj1dgAGdc1k3prtbC2t2L1tSmICg7pmMmVoDufk9WHigM4RilpERERERCQ6KNFtBZtKylm4rohPNpawcmMpO8qrKK8KAU5qUiLJicauyhClFVWsL9rFqs2lVIUcgMN7ZfO9E4Zw+phe9OmUDkDxrkqqqp205ATSkhI1eZSIiIiIiEgtMZ3olpZXUVpRRYd2KaQkJexevquymvyCbSzfUELN/EyrNpeypLCYLaUVdExPoXNGClOHdeXUUT3qvdWOu7N2WxlLCotZs62MjcW72FJaQVV1iIrqEEsKS1i1uXT39l0yU8hul0xqUiIAFdUhKqpCpCUnkJ6SRL/OGZwwvBtDurXn6IGd6ZqVtt97ZunWPyIiIiIiIgdk7h7pGJokLy/P8/Pz61wXCjkPz1rNLS8spaQ8fL/YzNQkOqQnk5WWzMpNO4Ie1T0yU5MY1r093bLS2F5WwZqtZazeupN2yYkM69GesopqSiuqCIUg5E7IneoQlFVUUVpRvbuclMQEOmemkJyYQFKiMTAnk7x+HRnTtyNDumXq2lkREREREZGDYGZz3D2vKa9tsz261SHnr2+t5Ln5hbuT1vSURDplpLK+uIyF64qZNKgzJ43ozvadlWzbWcn2nRVsL6tk4oBOHDs4h1G9s0kww4EO7ZL3GgLs7sxbs50n5qzlsy2l5GSmkpGaRGKCkWhGQgKYGSmJCQzulslhPbLI7ZxBx/TkBm/jIyIiIiIiIi2nzfbopvUY7N0vvI0xfTuQk5mKAzsrqtiyo4LqkHPV1EFMG91TSaeIiIiIiEgbFJc9uh0zUnjhO8dwWI+sSIciIiIiIiIiUSSh4U2iU68O7ZTkioiIiIiIyH7abKIrIiIiIiIiUhcluiIiIiIiIhJTlOiKiIiIiIhITFGiKyIiIiIiIjFFia6IiIiIiIjEFCW6IiIiIiIiElOU6IqIiIiIiEhMUaIrIiIiIiIiMUWJroiIiIiIiMQUJboiIiIiIiISU5ToioiIiIiISExRoisiIiIiIiIxRYmuiIiIiIiIxBQluiIiIiIiIhJTlOiKiIiIiIhITFGiKyIiIiIiIjFFia6IiIiIiIjEFCW6IiIiIiIiElOU6IqIiIiIiEhMUaIrIiIiIiIiMcXcPdIxNImZlQDLgqfZQNEhFhlLZXQBNkdBHM1VTkuXcbD11Rb2pSXLqaueomV/orGMQ/keRuP+tHQZ9dVXtOxLpGOpXUfRUifRUsaBymns9zBa9ieWvnvNVU60lBEtbay28n8Tj22shspQnTTOUHdv36RXunub/Afk13r812YoL5bKyI+GOKKsTg5YxsHWV1vYl5Ysp656ipb9icYyDuV7GI3709Jl1Fdf0bIvkY5Fv3uNL6ex38No2Z9Y+u61xTppan21tX1pjVjisY3VUBmqk0a/tsnfuVgZuvwfldHsmiuOaKkTldEy5aiM5i+jucpRGc1fRnOVozKav4zmKkdlNH8ZzVVOtJTRHKJpX6IlFpXRMuXEUhmN1paHLue7e16k44hGqpvGUX0dHNVT46i+Gkf11TDVUeOpzhqmOmoc1VfjqL72pzppnEOpr7bco/vXSAcQxVQ3jaP6Ojiqp8ZRfTWO6qthqqPGU501THXUOKqvxlF97U910jhNrq8226MrIiIiIiIiUpe23KMrIiIiIiIish8lum2MmbmZ/bPW8yQz22RmMyMZV1tgZjsiHUNb0VBdmdkbZhbX15eY2RnB93FYpGNpC8zsf81skZnNN7N5ZjYx0jFFIzPrbWbPmNknZrbSzP5sZin1bP9dM0tvzRijRfD9+2Ot5983sxsjGFLUMbPq4Pu2yMw+NrPrzUxtv4OgNsPBqfUZq/mXW8+2Md92UDu9aVqqTaWDXdtTCow0s3bB8xOAdRGMRyRenQe8A5wb6UCinZkdBZwKjHX3UcDxwJrIRhV9zMyAp4Cn3X0wMATIBH5Vz8u+C8RloguUA2eaWZdIBxLFytx9tLuPINxe+DLwiwjHJLGl5jNW868g0gFF2CG3080sqdmjin5NalOZWWJ965Xotk0vAKcEj88DHq1ZYWYTzOw9M5sb/B0aLH/bzEbX2u5dMxvVmkFHAzObUvusmpndYWYXBY8LzOz/zOwjM1sQ7z119dVVvDOzTGAScCnBQbmBz9aXzWypmb1jZtPj8MxuD2Czu5cDuPtmd//czMaZ2ZtmNsfMXjKzHrD7rP9twTFsoZlNiGj0recLwC53vx/A3auB64BLzCzDzP4QHJvmm9k1ZnYt0BN43cxej2DckVJFeJKS6/ZdYWb9zOy1oK5eM7O+ZpYdHOcTgm3SzWyNmSW3duCR4O4bgW8BV1tYopn93sxmB/V0ec22ZvaD4LP2sZn9NnJRR5aZZQafn5p2wbRgea6ZLTGze4Pe8pdrJTZx70DH9sDX4+DY3pR2+kVm9oSZ/Qd4ufVDjpx62lRvmdm/zWyxmd1d69i9w8xuMrMPgaPqK1uJbtv0GHCumaUBo4APa61bChzr7mOAnwO/Dpb/DbgIwMyGAKnuPr/VIm47Nrv7WOAvwPcjHYxErdOBF919ObDVzMYeaMPge3oPcLK7TwZyWifEqPIy0MfMlpvZXWZ2XJBc3A6c7e7jgPvYu+cyw92PBr4drIsHI4A5tRe4ezGwGrgM6A+MCXrFH3b36cDnwFR3n9rawUaJO4HzzSx7n+V3AP+oqStgursXAR8DxwXbnAa85O6VrRZthLn7p4Tbfl0JNyqL3H08MB74ppn1N7OTCR/jJrr7EcAtkYo3CuwCzgjaBVOBP5qZBesGA3cGveXbgbMiE2LEtbM9w5b/rWM70LR2OoSTtgvd/QutFml0OJ2621QTgO8BhwMDgTOD5RnAQnef6O7v1FdwPHaNt3nuPt/C10CcBzy/z+ps4EEzGww4UHOm+gngZ2Z2A3AJ8EDrRNvmPBX8ncOeL5TIvs4DbgsePxY8f+4A2w4DPnX3VcHzRwn3qsQNd99hZuOAYwg3Fh8HfgmMBF4J2o2JQGGtlz0avPYtM8sysw7uvr1VA299Rvi4XdfyY4G73b0KwN23tmZg0crdi83sH8C1QFmtVUex5xj+T/Yka48D5wCvE+45uKuVQo0mNYnaicAoMzs7eJ5NOHk7Hrjf3XdC3H/WDPi1mR0LhIBeQLdg3Sp3nxc8ngPktnp00aHM3UfXPDGzkcT5sb2J7XSAV+L0+3agNtWs4OQcZvYoMBn4F1ANPHkwBSvRbbueBf4ATAE611p+M/C6u58RfMneAHD3nWb2CjAN+CoQ05MB1KOKvUcypO2zvjz4W42+Hw3VVVwys86Eh5iONDMn/CPuhL+TddWXITXDcN8A3jCzBcBVwCJ3P9Cwo30Tvni4F94i9ukVMrMsoA/wKfFRB01xG/ARcH8929TU3bPAb8ysEzAO+G/LhhZdzGwA4d+3jYSPTde4+0v7bHMS+qzVOJ/wKJxx7l5pZgXsObaX19quGtDQ5TBDx3ZoZDs9UNpawUWLetpUz3Pgz8quoE3RIA1dbrvuA25y9wX7LM9mz0XvF+2z7m/AdGB2nJ4xAvgMGG5mqcFQty9GOqAoprqq29mEh0T2c/dcd+8D1PTW1lVfS4EBtmcmynNaN9zIM7OhwdnrGqOBJUCOhSeqwsySzWxErW3OCZZPJjy8sqi14o2g14B0M7sAdk+y8UfCI3BeBq6wYJKSIFEDKAHat36o0SP4PZtBeChujffYM6nJ+YQnOcHddwCzgD8DMw+2sRQLzCwHuBu4w90deAm4suYaZTMbYmYZhD9rl1gwm3etz1o8ygY2BknuVKBfpANqA5ahYzs0rZ0ejw7UppoMTAgup0gg/Lmpd5hyXeK9x6rNcve1hH+o93UL4SER17PPmWp3n2NmxdR/1jsmBY3DcndfY2YzgPnAJ8DcyEYWfVRXDToP2HdylieBrxFubO9VX+5eZmbfBl40s82EG9nxJhO43cw6EB4psILw8O2/AtODEwNJhHvmFgWv2WZm7wFZhC+3iHnu7mZ2BnCXmf2M8Mno54GfEO4xGgLMN7NK4F7C16H+FXjBzArj+DpdCJ8QuLrW82uB+4LLdTYBF9da9zjhy3mmtFp0kdPOzOYRHh5ZRXgY95+CdX8jPNz2o+C6003A6e7+ooUnr8w3swr2fAbjRs3vIOHru/9jZvnAPMInLqUe7l4RDIeP62N7U9rpcepAbaorgfeDdYcDbwH/bmzhFj6pJ/HAzHoSHiIxzN1DEQ6nVZnZEcC97h6rM/w1G9VV8zOzzOA6VSM8ec4n7n5rpOOKVmb2BvB9d8+PdCwiEn/0OygSWWY2hXA74NRDKUdDl+NEMBTuQ+B/4zDJvYLw5Ac/jXQs0U511WK+GfSqLCI8bOmeyIYjIiJ10e+gSOxQj66IiIiIiIjEFPXoioiIiIiISExRoisiIiIiccnM+pjZ62a2xMwWmdl3guWdzOwVM/sk+NsxWN452H6Hmd2xT1nnmdkCM5tvZi+aWZdI7JOIhGnosoiIiIjEJTPrAfRw94/MrD0wBzid8K1ftrr7b83sR0BHd/9hcAumMcBIYKS7Xx2UkwR8Dgx3981mdguw091vbPWdEhFAPboiIiIiEqfcvdDdPwoelxC+x3cvYBrwYLDZg4STX9y91N3fAXbtU5QF/zKCGfazCCe+IhIhuo+uiIiIiMQ9M8sl3Fv7IdDN3QshnAybWdf6XuvulWZ2JbAAKCV8P/WrWjZiEamPenRFREREJK6ZWSbwJPBddy9uwuuTgSsJJ8o9gfnAj5s1SBFpFCW6IiIiIhK3giT1SeBhd38qWLwhuH635jrejQ0UMxrA3Vd6eAKcGcDRLROxiBwMJboiIiIiEpeC62n/Dixx9z/VWvUscGHw+ELgmQaKWgcMN7Oc4PkJhK/3FZEI0azLIiIiIhKXzGwy8Dbha2tDweKfEL5OdwbQF1gNfMXdtwavKSA82VQKsB040d0Xm9kVwHeASuAz4CJ339JqOyMie1GiKyIiIiIiIjFFQ5dFREREREQkpijRFRERERERkZiiRFdERERERERiihJdERERERERiSlKdEVERERERCSmKNEVERFpIjPrbGbzgn/rzWxd8HiHmd3Vgu87xcyObqnyRURE2rqkSAcgIiLSVgX3yBwNYGY3Ajvc/Q+t8NZTgB3Ae63wXiIiIm2OenRFRESaWdDjOjN4fKOZPWhmL5tZgZmdaWa3mNkCM3vRzJKD7caZ2ZtmNsfMXjKzHsHya81ssZnNN7PHzCwXuAK4Lug9PsbMTjOzD81srpm9ambdGvneBWb2OzObFfwbFJGKExERaSZKdEVERFreQOAUYBrwEPC6ux8OlAGnBAnn7cDZ7j4OuA/4VfDaHwFj3H0UcIW7FwB3A7e6+2h3fxt4BzjS3ccAjwE/ONj3rrVdsbtPAO4Abmvm/RcREWlVGrosIiLS8l5w90ozWwAkAi8GyxcAucBQYCTwipkRbFMYbDMfeNjMngaePkD5vYHHg17gFGBVI967xqO1/t7a6D0UERGJIurRFRERaXnlAO4eAird3YPlIcInnQ1YFPTQjnb3w939xGCbU4A7gXHAHDOr6yT17cAdQU/t5UBaI967hh/gsYiISJujRFdERCTylgE5ZnYUgJklm9kIM0sA+rj764SHI3cAMoESoH2t12cD64LHFzYxhnNq/X2/iWWIiIhEBQ1dFhERiTB3rzCzs4HpZpZN+Pf5NmA58FCwzAhfl7vdzP4D/MvMpgHXADcCT5jZOuADoH8Twkg1sw8JnwQ/71D3SUREJJJszwgmERERiUdmVgDkufvmSMciIiLSHDR0WURERERERGKKenRFREREREQkpqhHV0RERERERGKKEl0RERERERGJKUp0RUREREREJKYo0RUREREREZGYokRXREREREREYooSXREREREREYkp/w89l/zf0YM9JwAAAABJRU5ErkJggg==</span><span class="s3">\n</span><span class="s2">"</span><span class="s0">,</span>
<span class="s2">"text/plain"</span><span class="s0">: [</span>
<span class="s2">"<Figure size 1152x648 with 1 Axes>"</span>
<span class="s0">]</span>
<span class="s0">},</span>
<span class="s2">"metadata"</span><span class="s0">: {</span>
<span class="s2">"needs_background"</span><span class="s0">: </span><span class="s2">"light"</span>
<span class="s0">},</span>
<span class="s2">"output_type"</span><span class="s0">: </span><span class="s2">"display_data"</span>
<span class="s0">}</span>
<span class="s0">],</span>
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